Basic Principles of IRT And Application to Practical

Transcription

Basic Principles of IRT
And
Application to Practical
Testing & Assessment
By Dr. V. Natarajan
1
About The Author
Dr. V. Natarajan
Professor Emeritus at MeritTrac Services. An engineer and
D.Litt. in Educational Evaluation and Administration,
guides the Test Development and Research teams in
MeritTrac. The author of 72 books, including an e-book
available
free
download
at
www.merittracblog.blogspots.com on Basic Principles of
IRT and Applications to Practical Testing and over 60
original papers published in Indian and International
Journals of repute, is a pioneer in the area of education
assessments in India. Also a visiting faculty at ETS,
Princeton, USA, and has been a member of the
Association of Indian Universities for over three decades.
He also is a member of Board of Governors of IACAT
from the last 5 years and member of the Governing body
of Chitkara University. He is a holder of 4 patents (IPRs)
in Engineering Design and in statistics for assessment.
You can write to the Dr. V. Natarajan at [email protected]
Copyright © Dr. V. Natarajan 2009
All Rights Reserved.
This book is self-published by the author, has been released only in an electronic format and is
accessible to MeritTracers, participants of 2008 IAEA conference and participants in the three annual
IACAT conferences held at Amsterdam, Asilomar (US), and the third one at Sydney (Australia)
conference been held in the near future. The author has allowed readers to freely distribute the book
provided no modifications are made to the book in the distribution and the authors are acknowledged in
all distributions. Please write to [email protected] for more information regarding distribution
of this book.
The author is grateful to Mr. Mohan Kannegal, co-founder MeritTrac Services and presently Chief
Technology Officer, Manipal Education Malaysia Sdn Bhd for rendering this word document into
Amazon website for and on behalf of MeritTrac Services.
2
Acknowledgement
It gives me immense pleasure to make my humble acknowledgements to all those who
have been instrumental in my getting knowledge and skills in the matter of IRT and
greatly indebted to my teacher Prof. Fred Lord, father of IRT, of ETS, who taught me the
basics and nuances of IRT and its applications to practical testing through a course
“Applications of IRT to Practical Testing” at ETS. To Dr. D.H.Lawley the whole praise
be given to have initiated the concept of item characteristic curve as early as 1943. He
triggered the great minds of researchers like Rasch, Birnbaum and Fred Lord for their
single, two and three parameter models. I have used most of what I learnt and was
inspired by the work of Benjamin Wright of Chicago, Frank Baker, Professor Emeritus
who pioneered the first e-book made available free of cost and his BIRT software. I had
used this software in our R&D work and included it in the appendix because no one
should miss an access to it and learn from it. I acknowledge profusely Lawrence Rudner,
Vice President of GMAC and a Consortium partner of MeritTrac for making available a
tutorial for computer adaptive testing that is very unique and brings forth adaptive testing
in its full perspective. My friends in NFER in U.K., Dr. Skurnik and Dr. Nuttall from
whose book I learnt all about Rasch Model. I am deeply indebted to all of these and my
own students who influenced me and this e-book could not have been made possible to
all interested. Finally, I would like to gratefully acknowledge the part played by both my
Senior Research Associates; Ms. Neha Jain for a lion’s share and Ms. Ruchika Girdhar
for helping to organize this revised version. I may conclude that they are deemed as coauthors.
Dr. V. Natarajan
Prof. Emeritus
MeritTrac Services (P) Ltd.
3
CONTENTS
Introduction to Modern Testing .........................
Classical Test Theory to Item Response Theory ...............
Contributions in the Area of IRT ...........................................
IRT over CTT ...........................................................................
Basic Concepts of IRT ............................................................
Plotting Ability versus Probability ..........................................
Examples ..................................................................................
Exercises ..................................................................................
Item Characteristic Curve Models ....................
Rasch’s Single Parameter Model .........................................
Example For Rasch Model ....................................................
Birnbaum’s Two Parameter Model .......................................
Example For Birnbaum’s Model ............................................
Fred Lord’s Three Parameter Model ....................................
Examples ..................................................................................
Interpretation of Item Parameters .........................................
Item Information Function .................................
Item Information Function of Single Parameter Model ......
Item Information Function of Two Parameter Model .........
Item Information Function of Three Parameter Model ......
Examples ..................................................................................
Test Characteristic Curve (Test Response Function) .......
Examples ..................................................................................
Test Information Function ......................................................
Interpreting the Test Information Function ..........................
Test Information Function of Single Parameter Model ......
Test Information Function of Two Parameter Model .........
Test Information Function of Three Parameter Model ......
Estimating Parameters .....................................
Procedure for Estimating Parameters ..................................
Examples ..................................................................................
Group Invariance of Item Parameters ..................................
Note ...........................................................................................
Examples ..................................................................................
Estimating a Test Taker’s Ability...........................................
Ability Estimation Parameters ...............................................
Item Invariance of a Test Taker’s Ability Estimate .............
Test Calibration ................................................
Test Calibration Process .........................................................
The Metric Problem .................................................................
Summary of the Test Calibration Process ............................
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The Likelihood Function ..........................................................
The Maximum Likelihood Estimate of Ability.......................
IRT Test & Item Analysis Using Software ...........
Examples ...................................................................................
Application Of IRT To Item Banking ...................
Application of IRT to Adaptive or Tailored Testing.....
Examples ..................................................................................
Future of Item Response Theory in India ............
APPENDIX........................................................
5
6
Introduction to Modern Testing
Classical Test Theory to Item Response Theory
Classical Test Theory, popularly known as CTT, started off as majority of practices developed
during the 1920’s. This theory has component theories like Theory of Validity, Theory of
Reliability, Theory of Objectivity, Theory of Test Analysis, Theory of Item Analysis etc. Most of
the practices were initially confined to psychological tests and later on extended to educational
testing. However, a new test theory had been developing over the past fifty years that was
conceptually more powerful than CTT. It is based upon items rather than test scores. This new
approach was known as Item Response Theory (IRT). While the basic concepts of IRT were,
and are, straightforward, the underlying mathematics was somewhat advanced compared to
that of CTT. It was difficult to examine some of these concepts without performing a large
number of calculations to obtain usable information using computer technology; the
advancement in one influenced the other considerably.
CTT is best suited for traditional testing situations, either in group or individual settings, in
which all the members of a target population are administered the same or parallel sets of test
items, for instance, test takers seeking admission in a college or recruitment to a job. These
item sets can be presented to the test taker in either a paper-and-pencil or a computer format.
Regardless of the format, it is important for the measurement of individual ability that the
items in each item set have “difficulties” that match the range of ability or proficiency in the
population. In addition, precise estimation of individual ability requires the administration of a
“large enough” number of items whose difficulty levels narrowly match the individual’s level of
ability or proficiency. For heterogeneous populations, these requirements of the “finite length”
test result in inefficient and wasteful testing situations that are certainly frustrating to the test
taker and not very valid and reliable from test administrator’s and analyst’s point of view.
Models for mental tests began to appear, as early as 1950’s. These addressed the problems
with CTT and exploited the emergence of computing technology. In fact, a powerful feature of
these newer testing models was the ability to choose test items appropriate to the test taker’s
level of proficiency during the testing session, i.e. to tailor the test to the individual in real
time. Today, the more popular and well developed of these models make up the family of
mathematical characterizations of a test taker’s test responses known as IRT. Although difficult
to implement in practice, IRT is the formulation of choice for modern testing.
Despite its popularity, CTT has a number of shortcomings that limit its usefulness as a
foundation for modern testing. The emerging role of computing technology in mental testing
highlights some of these limitations of CTT.
7
Contributions in the Area of IRT
Over the past century, many persons have contributed to the development of IRT. Three
persons deserve special mention and recognition. D.N. Lawley of the University of Edinburgh
published a paper in 1943 showing that many of the constructs of CTT could be expressed in
terms of parameters of the item characteristic curve that he talked about. This paper marks
the beginning of IRT as a measurement theory. The work of Dr. F.M. Lord of the Educational
Testing Service has been the driving force behind both the development of the theory and its
application for the past 50 years. Dr. Lord systematically defined, expanded and explored the
theory as well as developed computer programs needed to put the theory into practice. In the
late 1960s, Dr. Benjamin D. Wright of the University of Chicago recognized the importance of
the measurement work by the Danish mathematician Georg Rasch. Since that time, he has
played a key role in bringing item response theory, the Rasch model in particular, to the
attention of practitioners. Without the work of these three individuals, the level of
development of IRT would not be where it is today.
Frank Baker came out with an e-book on IRT in 1985. IRT was an upstart whose popular
acceptance lagged partly because the underlying statistical calculations were quite complex.
Baker’s contribution was to write a well written introductory text on IRT with software for the
then state-of-the art Apple II and IBM personal computers. This program freed the readers
from the tedious statistical calculations. At about the same time, Dr. Natarajan (India, 1984)
came up with a text on Sample free item analysis and addressed all three models of Rasch,
Birnbaum & Fred Lord. Fred Lord taught Dr. Natarajan through an international course, on
Applications of Item Response Theory to Practical Testing held in Princeton, ETS for a period
of 10 days wherein Dr. Natarajan came in to appreciate all the nuances of his three parameter
logistic model. More or less at the same time, Dr. Natarajan probed relentlessly the three
models and submitted a thesis on “Applications of Item Response Theory to finer
discrimination in Achievement Testing” and was awarded a D.Litt by Pune University in India.
Much has changed since 1985. IRT now powers the work of major U.S. test publishers and is
used as the basis for developing the National Assessment of Educational Progress, as well as
numerous state and local tests. In the UK the National Foundation for Educational Research
brought out a publication entitled “The Objective Interpretation Of Test Performance” and it
dealt with Rasch model and its applications. Ever since it has gained acceptance in the UK,
many testing organizations in the UK are adopting IRT and particularly the Rasch model for
item calibration and item analysis. Given its widespread acceptance, test administrators and
developers need just a basic understanding of the IRT model. Now more than 525
organizations including business, education and training are widely using IRT models for their
work. In India there are several leaders making use of IRT analysis for their merit lists in
admission tests (MIBE, AIIMS, CMC, REC to name only a few).
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IRT over CTT
The IRT is gaining in acceptance in psychological and educational testing because it provides
more adaptable and effective methods of test construction, analysis and scoring than those
derived from CTT. The source of its greater power is in the relationships it establishes between
properties of the items and the operating characteristics of the test made up of the items.
These relationships can be valid for actual tests of any length whereas any comparable results
in Classical Theory hold only for hypothetical test consisting of indefinitely many items.
The provision in IRT for treating the items or small sets of similar items, as the exchangeable
units of test construction and scoring has lead to numerous innovations in testing practice
especially item banking and adaptive testing (tailored testing). The former can appreciably
reduce the time and cost of producing a high quality operational test. The latter, either in the
form of computerized adaptive testing or two stage testing using paper and pencil instruments
enables testing time to be reduced to a half or a third of that required for a conventional test
of the same precision.
Equally important for long term testing and assessment programs is the ability to retire and
replace items in an operational test without altering the interpretation of the test scale.
Because IRT scale scores are functions of estimated item parameters, the scoring absorbs
possible differences in the characteristics (difficulty, discriminating power etc.) between the
retired items and the replacements. In this way, the need to find new items with the same
difficulty and discriminating power as the old items or for an equating study of the revised test
separate from its operational use, as required in Classical Theory, is eliminated.
Another property unique to IRT is the location of items and the test takers on the same scale.
The response models on which IRT models are based, enable the analyst to state the
probability that a test taker at a particular score level will answer a given item correctly. This
permits the “content referencing” of the scale scores. Typical items that test takers can answer
correctly with an assigned probability (for instance, 50% or 80%) illustrate the meaning of
various points on the scale in terms of task content.
Under CTT, the test taker’s raw test score would be the sum of the scores received on the
items in the test. Under IRT, the primary interest is in whether a test taker got each individual
item correct or not, rather than in the raw test scores. This is because the basic concepts of
IRT rest upon the individual items of a test rather than upon some aggregate of the item
responses such as a test score. Thus, it is clear that in CTT the whole test and the whole
group of test takers are considered together and all statistical quantities worked out. But in
IRT, the concern is the individual item and the individual test taker. An attempt is made to
relate the individual item characteristic to the individual’s ability which of course has a different
and a definite definition.
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Basic Concepts
Ability
In academic areas, one can use descriptive terms such as reading ability and arithmetic ability.
Each of these is what psychometricians refer to as an unobservable, or latent, trait. Although
such a variable is easily described, and knowledgeable test takers can list its attributes, it
cannot be measured directly as can height or weight, for example, since the variable is a
concept rather than a physical dimension. A primary goal of educational and psychological
measurement is the determination of how much of such a latent trait a test taker possesses at
a given point of time. Since most of the research has dealt with variables such as scholastic,
reading, mathematical, and arithmetic abilities, the generic term “ability” is used within IRT to
refer to such latent traits. To measure how much of this latent trait a test taker has, it is
necessary to have a scale of measurement.
IRT is also known as probabilistic theory since it deals with probability of possible response to
a test item. It derives the probability of each of these responses as a function of ability and
item parameters. Traditionally, the number right score on a multiple choice test seems to
indicate ability. But in IRT, the probability of the correct response to an item is summed for all
items answered correctly in a test indicating, the ability of the person taking the test.
Immaterial of the fact that the test taker answered correctly or wrongly
To measure an ability of a test taker, a test can be developed under IRT consisting of a
number of multiple choice items. Each of these items measures some facet of the particular
ability of interest. The test marker scoring the test must then decide whether the response he
is giving to the item is correct or not. When the item response is determined to be correct, the
test taker receives a score of one; an incorrect answer receives a score of zero i.e., the item is
dichotomously scored. Items scored dichotomously are often referred to as binary items.
Difficulty
A test based on IRT consists of items that are calibrated for its parameters. Therefore,
different items in a test will have different parameters. The most common parameter for an
item is its difficulty (item difficulty). The probability of getting a correct response by a test
taker with extremely low ability (-∞, -4 or -3) is 0 or almost 0, the probability of getting a
correct response by a test taker with extremely high ability (+∞, +4 or +3) will be almost 1,
tending towards 1 but not equal to 1. The ability corresponding to a probability of 0.5 is
defined as the item difficulty of the item. Thus, the item difficulty of an item and the ability of
the test taker are on the same scale. This is the unique characteristic of IRT models that
provide a true relationship between test items and true scores of test takers. For Rasch model,
10
it is invariably taken as the middle point of the item characteristic curve where the curve
shows a tendency of contra flexure that is bending in the opposite directions (there is a
common tangent that can be drawn at this point, which is the point of inflexion).
True Score
In the Classical Test Theory (CTT), the number right score, is taken to represent the level,
whereas the true score (if any, such exists) is the mean of great number of several such
scores of the test taker over the same or equivalent tests. One can easily realize that such a
true score, which is the mean of all such scores, is impractical or impossible to obtain. The
next best thing in CTT is to estimate a Standard Error of Measurement (SEM) and specify the
limits of any number right score. For example, if a test taker’s number right score is 72 and
SEM of the test is 7, the test taker’s score can range between 65 (72-7) to 79 (72+7) for 2/3rd
probability. This vitiates all arithmetical value judgments made and used of number right
scores. IRT enables the estimation of True Score (TS) from a test taker’s ability, with a low
percent of error (usually of the order of 0 .1 percent]
The probability of getting a correct
answer by a test taker is indicative of the maximum mean of the test takers scores if he takes
the item a great number of times let it be .75 [ let his scores be successively
1,1,0,1,0,0,1,1,1,1,1,1,1; the average works out to .75]
The true score for an estimated ability of a test taker (θ) is the sum total of probability of a
correct response of all the items (with different item difficulty values), that is,
TS (θ ) = ∑
of individual probability of correct answers (D.H Lawley)
This presupposes that test taker abilities of various test takers, taking a test of items of
various item difficulties are estimated in a given situation and that for an estimated given
value of test taker ability, the true score can be estimated. True scores for test takers once
determined are invariants and they are “item-free”. Similarly, item parameters like item
difficulty, item discrimination and guessing are all invariants for a given item and are “test
taker free”. The graph shown below depicts the ICC of a single item:
11
If an item with an invariant item difficulty is administered to group2 of very high ability,
responses will be all correct responses. The probability of such responses of the order of 0.5
and above nearing 1, the part of item characteristic curve that will be plotted belongs to the
higher end of the curve as shown below:
12
On the other hand, if the same item is administered to group1 of low ability, the probability of
correct responses will be much lower than 0.5 (that is, most of the test takers might get the
item wrong) and the lower end of the item characteristic curve as shown below:
13
Plotting Ability versus Probability
This ability score is denoted by the Greek letter theta, θ. At each ability level, there is a certain
probability that a test taker with that ability will give a correct answer to the item. This
probability is denoted by P (θ). A response to a binary test item “i” is indicated by the item
score Xi which can take the following forms:
X i = 1:
If the test taker answers it correctly
X i = 0:
If the test taker answers it incorrectly
By convention, the ability of the test taker is indicated by θ (theta) and probability of a correct
response to the item “i” is represented by:
P( X i = 1/ θ ) = Pi (θ )
And the probability of an incorrect answer is given by
P( X i = 0 / θ ) =1− Pi (θ )
For instance, an item says “What is the area of a circle with radius 3cm?” The options are
9cm2, 18.85cm2 and 28.28cm2. The first option is very naïve, second is wrong but implies
14
advanced knowledge and third is the correct one. Let’s assume that this item has been
calibrated and its psychometric properties look as shown in the graph for partial credit
model. In this example, there is one correct answer and two wrong answers. The probabilities
of the correct and the wrong answers are indicated in Figure 1-1 of the partial credit model:
Figure 1-1: The Partial Credit Model
The black curve is for the 1st response, blue one for the 2nd response and red one for the 3rd
response. The person’s ability, denoted byθ, is plotted along the horizontal axis. The
probability for each response, denoted by P (θ), is plotted along the vertical axis. The sum of
3 probabilities at each value of θ is 1. For the 1st response, which is totally irrelevant, the
probability is very high at low ability and drops down as the ability increases and the person
becomes more knowledgeable. The probability of 2nd response rises with ability to a certain
point and then drops down. The probability of the 3rd and correct response is small at low
ability levels but rises as ability increases. But, at any ability level the person still have a nonzero probability of selecting any response.
This can be simplified by lumping together the 2 wrong options so that we have a wrong and
a correct response (dichotomous item) as shown in Figure 1-2:
15
Figure 1-2
The black curve is for the wrong option and the red one for the correct option. As ability
increases the probability of a correct option increases but the probability of the wrong option
decreases. At any value of θ the sum of the 2 probabilities is 1. Therefore, the probability of
the wrong option is 1- P (θ).
Item Characteristic Curves (ICC)
In the case of a typical test item, at any value of the ability, the probability of the correct
option that is P (θ) will be small for test takers of low ability and large for test takers of high
ability. If one plotted P (θ) as a function of ability, the result would be a smooth S-shaped
curve such as shown in Figure 1-3:
16
Figure 1-3 : A typical item characteristic curve
The probability of correct response is near zero at the lowest levels of ability. It increases until
at the highest levels of ability, the probability of correct response approaches 1. This S-shaped
curve describes the relationship between the probability of correct response to an item and the
ability scale. In IRT, it is known as the item characteristic curve (ICC). This is also called Item
Response Function (IRF). Each item in a test will have its own ICC since every item in a test
has a different difficulty value.
The ICC is the basic building block of item response theory; all the other constructs of the
theory depend upon this curve. There are two technical properties of an ICC that are used to
describe it. The first is the difficulty of the item. Under IRT, the difficulty of an item describes
where the item functions along the ability scale. For example, an easy item functions among
the low-ability test takers and a hard item functions among the high-ability test takers; thus,
difficulty is a location index. The second technical property is discrimination, which describes
how well an item can differentiate between examinees having abilities below the item location
and those having abilities above the item location. This property essentially reflects the
steepness of the ICC in its middle section. The steeper the curve, the better the item can
discriminate. The flatter the curve, the less the item is able to discriminate since the
probability of correct response at low ability levels is nearly the same as it is at high ability
levels. Using these two descriptors, one can describe the general form of the ICC. These
descriptors are also used to discuss the technical properties of an item. But these two
properties say nothing about whether the item really measures some facet of the underlying
ability or not; that is a question of validity. These two properties simply describe the form of
the ICC. It was mentioned elsewhere that validity of a test item is something that depends on
the consideration that whether this particular item is constructed to reflect and provide an
evidence of achievement of an objective/outcome of learning the content. This process is
17
known as building in validity at the micro level. An item is valid since it is made to measure
exactly what it is meant to measure.
In Figure 1-4, three ICC’s are presented on the same graph. All have the same level of
discrimination but differ with respect to difficulty. The left-hand curve represents an easy item
because the probability of correct response is high for low-ability test takers and approaches 1
for high-ability test takers. The center curve represents an item of medium difficulty because
the probability of correct response is low at the lowest ability levels, around .5 in the middle of
the ability scale and near 1 at the highest ability levels. The right-hand curve represents a
hard item. The probability of correct response is low for most of the ability scale and increases
only when the higher ability levels are reached. Even at the highest ability level shown (+3),
the probability of correct response is only .8 for the most difficult item as shown in Figure 1-4:
Figure 1-4 : Three item characteristic curves with the same discrimination but different levels of difficulty
The concept of discrimination is illustrated in Figure 1-5. The figure contains three item
characteristic curves having the same difficulty level but differing with respect to
discrimination. The upper curve has a high level of discrimination since the curve is quite steep
in the middle where the probability of correct response changes very rapidly as ability
increases. Just a short distance to the left of the middle of the curve, the probability of correct
response is much less than 0.5, and a short distance to the right the probability is much
greater than 0.5. The middle curve represents an item with a moderate level of discrimination.
The slope of this curve is much less than the previous curve and the probability of correct
response changes less dramatically than the previous curve as the ability level increases.
However, the probability of correct response is near zero for the lowest-ability examinees and
near 1 for the highest ability examinees. The third curve represents an item with low
discrimination. The curve has a very small slope and the probability of correct response
18
changes slowly over the full range of abilities shown. Even at low ability levels, the probability
of correct response is reasonably large, and it increases only slightly when high ability levels
are reached. (Although the figures only show a range of ability from -3 to +3, the theoretical
range of ability is from negative infinity to positive infinity.) However, Dr. Natarajan (1984)
recommended -4 to +4 as the limits since these will include 99.9% of observations. Thus, all
the item characteristic curves of the type used here actually become asymptotic to a
probability of zero at one tail and to 1.0 at the other tail as shown in Figure 1-5:
Figure 1-5 : Three item characteristic curves with the same difficulty but with different levels of discrimination
Item characteristic curve of an item with a perfect discrimination is illustrated in Figure 1-6.
The item characteristic curve of such an item is a vertical line at some point along the ability
scale. To the left of the vertical line at θ = 1.5, the probability of correct response is zero; to
the right of the line, the probability of correct response is 1. Thus, the item discriminates
perfectly between examinees whose abilities are above and below an ability score of 1.5. Such
items would be ideal for distinguishing between examinees with abilities just above and below
1.5. However, such an item neither makes distinction among those examinees with abilities
above 1.5 nor among those examinees with abilities below 1.5 as shown in Figure 1-6:
19
Figure 1-6 : An item that discriminates perfectly at θ=1.5
Examples
Some graphical examples (taken out through BIRT software) are shown below that illustrate
the relation of ICC with difficulty and discrimination. In these examples difficulty has the
following five different levels:
•
•
•
•
•
Very easy
Easy
Medium
Hard
Very hard
And discrimination has the following five different levels:
•
•
•
•
•
None
Low
Moderate
High
Perfect
1. This example shows an item characteristic curve of an item with an easy difficulty
and high discrimination. As seen here, when item discrimination is greater than
moderate, the curve is S-shaped and rather steep in the middle.
20
2. This example shows an item characteristic curve of an item with hard difficulty and
low discrimination. As seen here, when item difficulty is greater than medium, most
of the curve has a probability of correct response that is less than 0.5.
3. This example shows an item characteristic curve of an item with medium difficulty
and low discrimination. As seen here, when item discrimination is less than moderate
the curve is nearly linear and appears rather flat.
21
4. This example shows an item characteristic curve of an item with medium difficulty
and moderate discrimination.
5. This example shows an item characteristic curve of an item with very easy difficulty
and moderate discrimination. As seen here, when item difficulty is less than
medium, most of the curve has a probability of correct response greater than 0.5.
22
6. This example shows an item characteristic curve of an item with no discrimination.
As seen here, no discrimination with any choice of difficulty level yields a horizontal line
at a value of P(θ)=0.5. This is because the value of the item difficulty for an item with
no discrimination is undefined.
23
Thus, regardless of the item discrimination, item difficulty of an item locates the item along
the ability scale. Therefore, item difficulty and discrimination are independent of each other.
Exercise
Using the BIRT software, find and plot the ICC for the following combination of item difficulty
and item discrimination:
1. Very easy difficulty and discrimination level as –
Low
High
Perfect
2. Easy difficulty and discrimination level as –
None
Low
Moderate
Perfect
3. Moderate difficulty and discrimination level as –
None
High
Perfect
4. High difficulty and discrimination level as None
Moderate
High
Perfect
5. Perfect difficulty with discrimination level as –
None
Low
Moderate
High
Perfect
24
Item Characteristic Curve Models
The central features of IRT are the three Item Characteristic Curve models for the item
characteristic curve. They are:
•
•
•
Rasch (Single Parameter) Model
Birnbaum (Two Parameter) Model
Fred Lord (three Parameter Model)
These models provide a mathematical equation for the relation of the probability of correct
response to ability. These mathematical expressions give the probability of a correct response
to a test item as a function of the ability. The models employ one or more parameters whose
numerical values define a particular item characteristic curve. They provide a vehicle for
communicating information about an item’s technical properties.
•
•
•
Single Parameter – Rasch Model
Two Parameter – Birnbaum Model
-
Item difficulty ‘b’
Item difficulty ‘b’
Item discrimination ‘a’
Three Parameter – Fred Lord Model - Item difficulty ‘b’
Item discrimination ‘a’
Item guessing ‘c’
Every item has invariant item parameters.
All the three models together integrated in a single graph are shown below:
25
Pi (θ)
(probability
of getting
+1.0
answer
right on any
item I with
ability θ) 1-c
0.5
α
tan α = a
c
Item Difficulty ‘b’
-∞
-4
-3
+∞
+4
+3
Rasch’s Single Parameter Model
Pi (θ ) = e a (θ −b ) /1 + e a (θ −b )
Where e=2.718, base of a natural log
a=scale constant determining the units of θ (For Rasch it is 1)
b=location parameter related to the difficulty of the item i (also referred
threshold)
to as item
The modified equation for Rasch model after rationalizing the numerator and the denominator
by multiplying with e-a(θ-b)
Pi (θ ) = 1/(1 + e −1(θ −b ) )
Note: The items with larger values of bi are more difficult; those with smaller values are
comparatively easier.
26
Pi (θ)
(probability
of getting
answer
+1.0
right on any
item I with
ability θ)
0.5
c
Example
1. Let us look at an item with item difficulty as -2.40 and a person with ability as +1.0.
This person will have a probability = 0.968. Calculation for the same is shown below: a
value for Rasch is 1
Pi (θ = +1.0) = 1/(1 + e −1(1−( −2.4)) )
= 1/(1 + e −1(1+ 2.4) )
= 1/(1 + e −3.4 )
= 0.968
Similarly, the calculations are carried out for all values of θ=(-3, -2, -1, 0, +1, +2, +3).
27
-( θ-b)
LOGIT calculated above is taken as θ-b and EXP(-L) is e
below:
. The ICC for this item is given
2. Let us look at another item with item difficulty as 0 and test takers with varying ability
like -3, -2.9………….+3 at intervals of 0.1.[ Note; ability 0 is not 0 ability but on scale of
-3 to +3 it is an average ability]. The format given in the table below helps in easy
calculations:
28
θi
b
(θi-b)=L
e-L
1+e-L
1/(1+e-L)
-3.0
0.0
[-3-(-0)]=-3
e3
1+e3
1/(1+e3)=
-2.9
0.0
[-2.9-(-0)]=-2.9
e2.9
1+e2.9
1/(1+e2.9 )=
+3.0
0.0
[3-(-0)]=3
e-3
1+e-3
1/(1+e-3)=
The above table of calculations can be easily performed on an excel sheet.
Birnbaum’s Two Parameter Model
In the Two Parameter model, at the point of contra flexure (inflexion) corresponding to 0.5
probability value, a common tangent is drawn and the slope of the tangent is designated as
“item discrimination” and this value is indicated by the letter “a”. The “b” and “a” value are
estimated for the given items. The equation to the curve is:
Pi (θ ) = e a (θ −b ) /(1 + e a (θ −b ) )
Where Pi(θ) = Probability of getting the correct answer to item i of a person with ability θ
θ = Person ability
b = Item difficulty
a = Item Discrimination
The modified equation for Birnbaum model after rationalizing the numerator and the
denominator by multiplying with e-a(θ-b)
29
Pi (θ ) = 1/(1 + e − a (θ −b ) )
Pi (θ)
(probability
of getting
answer
+1.0
right on any
item I with
ability θ)
0.5
α
tan α = a
c
Example
1. Let us look at an item with item difficulty as 0 and a=1.25, ability as +1.0. This person
will have a probability = 0.777. Calculation for the same is shown below:
Pi (θ ) = 1/(1 + e − a (θ −b ) )
= 1/(1 + e −1.25(1−0) )
= 1/(1 + e −1.25 )
= 0.777
30
-( θ-b)
below:
2. Let us look at another item with item difficulty as 0, a=1.25 and test takers with varying
ability like -3, -2.9………….+3 at intervals of 0.1.
31
θi
b=0.0
a=1.25
a(θi-b)=L
e-L
1+e-L
1/(1+e-L)=
Piθi
-3.0
0.0,
1.25
1.25[-3-(0.0)]=
-3.75
e3.75
1+e3.75
1/(1+e3.75)=
0
0.0
1.25
1.25[0-0]=0
e0
1+e0=2
½=0.5
+3.0
0.0,
1.25
1.25[3-0]=3.75
e-3.75
1+e-3.75
1/(1+e-3.75)=
FredLord’s Three Parameter Model
In the Three Parameter model, there is in addition, a third parameter called guessing for the
item and is designated by the letter “c”. This is given by the intercept of the probability axis
that indicates the probability of guessing the right answer. The guessing parameter is unique
to the item and is independent of test taker ability. Thus the guessing parameter remains a
constant for all test takers of various abilities. The equation for the curve is:
Pi (θ ) = c + (1 − c)[e a (θ −b ) /1 + e a (θ −b ) ]
32
Where Pi(θ) = Probability of getting the correct answer to item
person with ability θ
θ = Person ability
b = Item difficulty
a = Item Discrimination
c = Guessing Parameter
i
of
a
The modified equation for Birnbaum model after rationalizing the numerator and the
denominator by multiplying with e-a(θ-b):
Pi (θ ) = c + (1 − c)[1/1 + e − a (θ −b ) ]
The dotted line curve given below is for the Three Parameter (Lord’s) model:
Pi (θ)
(probability
of getting
answer
+1.0
right on any
item I with
ability θ)
0.5
α
tan α = a
c
Example
1. Let us look at an item with item difficulty as b= 0 , a=1.25,and c=0.25, withability as
+1.0. This person will have a probability=0.832. Calculation for the same is shown
below:
Pi (θ ) = c + (1 − c)[1/1 + e − a (θ −b ) ]
= 0.25 + (1 − 0.25) *[1/1 + e −1.25(1−0) ]
33
= 0.832
-( θ-b)
below:
34
2. Let us look at another item with item difficulty as 0, a=0.75, c=0.15 and test takers
with varying ability like -3, -2.9………….+3 at intervals of 0.1.
θi
a=0.75
b=0.0
c=0.15
a(θi-b)=L
e-L
(1-c)/
1+e-L
c+(1-c)/
(1+e-L)
-3.0
0.75,
0.0,
0.15
0.75[-3-0]=-2.25
e2.25
1-0.15/
1+e2.25
0.15+0.85/
(1+e2.75)=
0
0.75,
0.0,
0.15
0.75[0]=0
e0
0.85/
1+1
0.15+0.85/
(1+1)=
+3.0
0.75,
0.0,
0.15
e-2.25
0.85/
1+e-2.25
0.15+0.85/
(1+e-2.25)=
0.75[3-0]=-2.25
The Three Parameter (Fred Lord’s) model estimates are more accurate than the Two
Parameter (Birnbaum’s) model while the Single Parameter (Rasch’s) model is least accurate.
35
Interpretation of Item Parameters
Instead of verbal labels used earlier in describing the technical properties of an ICC, item
parameters can be used to do the same. These parameters have numerical values that have
intrinsic meaning. Interpreting these values and conveying this interpretation to a nontechnical audience is the next task to be carried out. The verbal labels used to describe an
item’s discrimination can be related to ranges of values of the parameter as follows:
Verbal Label
None
Very low
Low
Moderate
High
Very high
Perfect
Range of Values
0
0.01 to 0.34
0.35 to 0.64
0.65 to 1.34
1.35 to 1.69
> 1.70
+ infinity
These relations hold when one interprets the values of the discrimination parameter under a
logistic model for the ICC. If interpretation of the discrimination parameter under a normal
ogive model is required then these values need to be divided by 1.7.
Establishing an equivalent table for the values of the item difficulty parameter poses some
problems. The drawback of item difficulty, as defined under CTT, was that it was defined
relative to a group of test takers. Thus, the same item could be easy for one group and hard
for another group. Under IRT, an item’s difficulty is a point on the ability scale where the
probability of correct response is .5 for Single and Two Parameter models and (1 + c)/2 for a
Three Parameter model. Because of this, the verbal labels used earlier have meaning only with
respect to the midpoint of the ability scale. The proper way to interpret a numerical value of
the item difficulty parameter is in terms of where the item functions on the ability scale. The
discrimination parameter can be used to add meaning to this interpretation. The slope of the
ICC is at a maximum at an ability level corresponding to the item difficulty. Thus, the item is
doing its best in distinguishing between test takers in the neighborhood of this ability level.
Because of this, one can speak of the item functioning at this ability level.
For example, an item whose difficulty is -1 functions among the lower ability test takers. A
value of +1 denotes an item that functions among higher ability test takers. Again, the
underlying concept is that the item difficulty is a location parameter. Under a Three Parameter
model, the numerical value of the guessing parameter c is interpreted directly since it is a
probability. For example, c=0.12 simply means that at all ability levels, the probability of
getting the item correct by guessing alone is 0.12.
36
Item Information Function
Any item in a test provides some information about the ability of the examinee, but the
amount of this information depends on how closely the difficulty of the item matches the
ability of the person.
Item Information Function of Single Parameter Model
In the case of the Single Parameter model, the item information function depends upon how
closely the difficulty of the item matches the ability of the person, while in other models it
combines with other factors. The item information function of this model is shown below:
I i (θ , bi ) = Pi (θ , bi ) * Qi (θ , bi )
It is easy to see that the maximum value of the item information function is 0.25. It occurs at
the point where the probabilities of a correct and of an incorrect response are both equal to
0.5. Any item in this model is most informative for examinees whose ability is equal to the
difficulty of the item. As ability becomes either smaller or greater than the item difficulty, the
item information decreases. This is shown in Figure 2-1 below:
The most important practical implication of this is that we need items of different difficulty if
we are to achieve good measurement for people having all sorts of different abilities.
37
Item Information Function of Two Parameter Model
The item information function for the Two Parameter model is as shown below:
I i (θ , bi , ai ) = ai2 Pi (θ , bi ) * Qi (θ , bi )
The discrimination parameter ai is the second parameter that has quite a strong influence
because it appears in the formula as a square. This means that discrimination parameters
below 1 can decrease the information function rather dramatically, while discrimination
parameters above one will increase it substantially.
The item response functions are plotted with dotted lines and matched in color with the
corresponding item information functions, as shown in the above graph. The item information
functions still attain their maxima at item difficulty. However, their shapes and the values of
the maxima depend strongly on the discrimination parameter. When discrimination is high
(and the item response function is steep), the item provides more information on ability, and
the information is concentrated around item difficulty. Items with low discrimination
parameters are less informative, and the information is scattered along a greater part of the
ability range.
38
Item Information Function of Three Parameter Model
The item information function of the Three Parameter model is a bit more complicated as
compared to the Single Parameter or Two Parameter model. The item information functions of
the three models are shown below:
Single Parameter Model :
Two Parameter Model
:
Three Parameter Model :
I i (θ , bi ) = Pi (θ , bi ) * Qi (θ , bi )
I i (θ , bi , ai ) = ai2 Pi (θ , bi ) * Qi (θ , bi )
2
[
P
(
θ
−
c
)]
Q
(
θ
)
I (θ , a, b, c) = a 2
P (θ ) (1 − c)
The graph shown above has been plotted with two items. The item with the black lines has
a=1, b=-1, and c=0.1, while the item with the red lines has a=1, b=+1, and c=0.3. The b
parameter shifts the item information function to the left or to the right but does not affect its
shape. The two items have the same a=1 but differ in c. Hence, a higher c leads to an overall
decrease in item information. A further complication is that the item information function no
longer peaks at θ=b.
39
Examples
Let us look at the following items. The parameter values and the ICCs according to the Two
Parameter model (BILOG output) for the same are given below:
1. For Item #1, a=1.42, b=1.50, c=0. At the b value of 1.50 the probability of getting the
right answer Pi(θ) is 0.5. The information function at this point is calculated as shown
below:
(1.42 * 1.42) * (0.5 * 0.5) = 0.5041.
This shows that the peak of the information function as shown in the
graph. This
means that this particular item gives maximum information at
this ability of the test taker
and difficulty of the item. For any other ability, ranging from +1 to +2.5 this item can be
supposed to give
average information.
The graphs shown in green color hereinafter are those outputs of using BILOG 3
software:
Item Response Function and Item Information
Subtest 1: SAMP1 ;
a = 1.42;
b = 1.50;
Item 1: 0001
c = 0.00;
2
1.0
0.9
0.8
0.6
0.5
1
0.4
Information...
PROB (Correct)
0.7
0.3
0.2
0.1
0
-3
b
-2
-1
0
Scale Score
1
2
3
0
Metric Type
Normal
40
However, using BILOG-MG 3, the latest software from Scientific Software International Inc.,
the following ICC and Information curves are generated for all the three parameters.
1 Parameter Model
ItemInformation Curve: ITEM0001
ItemCharacteristic Curve: ITEM0001
a = 0.713
b = -1.020
0.14
1.0
0.12
0.8
In fo r m atio n
P r o b ab ility
0.10
0.6
0.4
0.08
0.06
0.04
0.2
0.02
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
1-Parameter Model, Logistic Metric
0
1
2
3
Scale Score
Ability
Item: 1
The parameter a is the item discriminating power, the reciprocal (1/a) is the item
dispersion, and the parameter b is an item location parameter.
41
2 Parameter Model
Item Information Curve: ITEM0002
Item Characteristic Curve: ITEM0002
a = 1.555
b = 0.351
1.0
1.0
0.9
0.8
0.8
In fo rmatio n
Pro b ab ility
0.7
0.6
0.4
0.6
0.5
0.4
0.3
0.2
0.2
b
0
-3
-2
-1
0.1
0
1
2
0
-3
3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 1
The parameter a is the item dis c riminating power, the rec iproc al (1/a) is the item
dis pers ion, and the parameter b is an item loc ation parameter.
3 Parameter Model
a = 7.980
b = 0.713
c = 0.201
1.0
12
10
0.8
In fo r m atio n
Pr o b ab ility
8
0.6
0.4
c
6
4
0.2
2
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 1
dis pers ion, b is an item loc ation parameter and c the gues s ing parameter.
42
right answer Pi(θ) is 0.5. The information function at this point is (1.42 * 1.42) * (0.5 *
0.5) that is 0.5041. This shows that the peak of the information function as shown in
the graph. This means that this particular item gives maximum information at this
ability of the test taker and difficulty of the item. For any another ability, ranging from 0.5 to +1.5 this item can be supposed to give average information.
Subtest 1: SAMP1 ;
a = 1.42;
b = 0.42;
Item 2: 0002
c = 0.00;
2
1.0
0.9
0.8
0.6
1
0.5
0.4
Information...
PROB (Correct)
0.7
0.3
0.2
0.1
0
-3
b
-2
-1
0
Scale Score
1
2
3
0
Metric Type
Normal
43
1 Parameter Model
a = 0.713
b = 0.534
0.14
1.0
0.12
0.8
Information
0.4
0.08
0.06
0.04
0.2
0.02
b
0
-3
-2
-1
0
1
2
0
-3
3
-2
-1
0
Ability
1
2
3
Scale Score
Item: 2
The parameter a is the item dis c riminating pow er, the rec iproc al (1/a) is the item
2 Parameter Model
a = 1.555
b = 0.351
1.0
1.0
0.9
0.8
0.8
In fo rmatio n
0.7
Pro b ab ility
Probability
0.10
0.6
0.6
0.4
0.6
0.5
0.4
0.3
0.2
0.2
b
0
-3
-2
-1
0
0.1
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 1
44
3 Parameter Model
a = 7.980
b = 0.713
c = 0.201
1.0
12
10
0.8
In fo r m atio n
Pr o b ab ility
8
0.6
0.4
c
6
4
0.2
2
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 1
dis pers ion, b is an item loc ation parameter and c the gues s ing parameter.
ability of the test taker and difficulty of the item. For any another ability, ranging from
+1.5 to +3 this item can be supposed to give average information.
45
Subtest 1: SAMP1 ;
a = 1.42;
b = 2.29;
Item 3: 0003
c = 0.00;
2
1.0
0.9
0.8
0.6
0.5
1
0.4
Information...
PROB (Correct)
0.7
0.3
0.2
0.1
b
0
-3
-2
-1
0
Scale Score
1
2
3
0
Metric Type
Normal
1 Parameter Model
a = 0.713
b = 0.557
0.14
1.0
0.12
0.8
0.10
Information
Probability
0.6
0.4
0.08
0.06
0.04
0.2
0.02
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
A bility
0
1
2
3
S cale S cor e
Item: 3
46
2 Parameter Model
a = 1.555
b = 0.351
1.0
1.0
0.9
0.8
0.8
0.7
Information
Probability
0.6
0.4
0.6
0.5
0.4
0.3
0.2
0.2
b
0
-3
-2
-1
0.1
0
1
2
0
3
-3
-2
-1
0
A bility
1
2
3
S cale S cor e
Item: 2
3 Parameter Model
a = 8.105
b = 0.899
c = 0.203
12
1.0
10
0.8
8
Information
Probability
0.6
0.4
c
6
4
0.2
2
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
S cale S cor e
A bility
Item: 2
dispersion, b is an item location parameter and c the guessing parameter.
47
ability of the test taker and difficulty of the item. For any another ability, ranging from 0
to +2 this item can be supposed to give average information.
Subtest 1: SAMP1 ;
a = 1.42;
b = 0.92;
Item 4: 0004
c = 0.00;
2
1.0
0.9
0.8
0.6
0.5
1
0.4
Information...
PROB (Correct)
0.7
0.3
0.2
0.1
0
-3
b
-2
-1
0
Scale Score
1
2
3
0
Metric Type
Normal
48
1 Parameter model
a = 0.713
b = 1.082
0.14
1.0
0.12
0.8
0.10
Information
Probability
0.6
0.4
0.08
0.06
0.04
0.2
0.02
b
0
-3
-2
-1
0
1
2
0
3
-3
-2
-1
0
A bility
1
2
3
S cale S cor e
Item: 4
2 Parameter Model
a = 1.938
b = 0.665
1.0
1.0
0.9
0.8
0.8
0.7
Information
Probability
0.6
0.4
0.6
0.5
0.4
0.3
0.2
0.2
b
0
-3
-2
-1
0
0.1
1
2
3
0
-3
-2
-1
0
1
2
3
S cale S cor e
A bility
Item: 3
49
3 Parameter Model
a = 8.195
b = 0.834
c = 0.163
1.0
12
10
0.8
8
Information
Probability
0.6
0.4
6
4
c
0.2
2
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
S cale S cor e
A bility
Item: 3
5. For Item #5, a=1.42, b=-0.28, c=0. At the b value of -0.28 the probability of getting
the right answer Pi(θ) is 0.5. The information function at this point is (1.42 * 1.42) *
(0.5 * 0.5) that is 0.5041. This shows that the peak of the information function as
shown in the graph. This means that this particular item gives maximum information at
this ability of the test taker and difficulty of the item. For any another ability, ranging
from -1 to +1 this item can be supposed to give average information.
50
Subtest 1: SAMP1 ;
a = 1.42;
b = -0.28;
Item 5: 0005
c = 0.00;
2
1.0
0.9
0.8
Information...
PROB (Correct)
0.7
0.6
0.5
1
0.4
0.3
0.2
0.1
b
0
-3
-2
-1
0
Scale Score
1
2
3
0
Metric Type
Normal
1 Parameter Model
a = 0.713
b = -0.504
0.14
1.0
0.12
0.8
0.10
Information
Probability
0.6
0.4
0.08
0.06
0.04
0.2
0.02
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
S cale S cor e
A bility
Item: 5
51
2 Parameter Model
a = 1.844
b = -0.338
1.0
1.0
0.9
0.8
0.8
0.7
Information
Probability
0.6
0.4
0.6
0.5
0.4
0.3
0.2
0.2
b
0
-3
-2
0.1
-1
0
1
2
0
3
-3
-2
-1
A bility
0
1
2
3
S cale S cor e
Item: 4
3 Parameter Model
a = 8.057
b = -0.012
c = 0.186
1.0
12
10
0.8
8
Information
Probability
0.6
0.4
6
4
c
0.2
2
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
S cale S cor e
A bility
Item: 4
52
In general terms, for a Two Parameter ICC model, the item information function is defined as
shown below:
I i (θ ) = ai2 Pi (θ )Qi (θ )
Where ai is the discrimination parameter for item i
Pi(θ) = 1/ (1+ EXP (-ai (θ - bi)))
Qi(θ) =1 - Pi (θ)
θ is the ability level of test taker
The amount of item information will be computed at seven ability levels for an item having
parameter values of b=1.0 and a=1.5 as shown below in the table:
θ
L
EXP(-L)
-3
-2
-1
0
1
2
3
-6
-4.5
-3.0
-1.5
0.00
1.5
3.0
403.43
90.02
20.09
4.48
1.0
0.22
0.05
1/1+
(e-L)=
Pi(θ)
0.00
0.01
0.05
0.18
0.50
0.82
0.95
Qi(θ)
Pi(θ) * Qi(θ)
a2
Ii(θ)
1.00
0.99
0.95
0.82
0.50
0.18
0.05
0.00
0.01
0.05
0.15
0.25
0.15
0.05
2.25
2.25
2.25
2.25
2.25
2.25
2.25
0.00
0.02
0.11
0.34
0.56
0.34
0.11
Calculation of item information function under a Two Parameter model for an item b=1.0, a=1.5
This item information function increases rather smoothly as ability increases and reaches a
maximum value of .56 at an ability of 1.0. After this point, it decreases. The obtained item
information function is symmetrical about the value of the item’s difficulty parameter. Such
symmetry holds for all item information functions under Single and Two Parameter models.
When only a single item is involved and the discrimination parameter has a moderate value,
the magnitude of the amount of item information is quite small.
Similar calculations can be carried out for item information function under Single and Three
Parameter models. The equations to item information function under these models are given
below:
53
I i (θ ) = Pi (θ )Qi (θ )
2
Q
(
θ
)
P
(
θ
)
−
c
I i (θ ) = a 2 [ i ][ i
]
2
Pi (θ ) (1 − c )
Where Pi(θ) = c+(1-c)(1/(1+ EXP (-L)))
L = a(θ-b)
Qi =1 - Pi (θ)
Exercise
1.Given an item with item difficulty b=-2,calculate the item information function ordinates for
a single parameter(Rasch Model) ,at various ability levels of -3,-2,-1,0,1,2,3 using BIRT
software and the appropriate formula for the item information function. Also plot the item
information curve.
2. Given an item with item difficulty b=-2,and item discrimination a=1.42,calculate the item
information function ordinates for a 2 parameter(Birnbaum Model) ,at various ability levels of 3,-2,-1,0,1,2,3 using BIRT software and the appropriate formula for the item information
function. Also plot the item information curve.
3.Given an item with item difficulty b=-2, item discrimination a=1.42,and guessing parameter
c=0.2 ,calculate the item information function ordinates for a 3 parameter(Fred Lord Model)
,at various ability levels of -3,-2,-1,0,1,2,3 using BIRT software and the appropriate formula
for the item information function. Also plot the item information curve.
Test Characteristic Curve (Test Response Function)
IRT is based upon the individual items of a test, and up to this point, we have dealt with the
items one at a time. Now, attention will be given to dealing with all the items in a test all at
once. When scoring a test, the response made by a test taker to each item is dichotomously
scored. A correct response is given a score of 1, and an incorrect response a score of 0; the
test taker’s raw test score is obtained by adding up the item scores. This raw test score will
always be an integer number and will range from 0 to N (N is the number of items in the test).
If test takers were to take the test again, assuming they did not remember how they
54
previously answered the items, a different raw test score would be obtained. Hypothetically, a
test taker could take the test a great many times and obtain a variety of test scores. One
would anticipate that these scores would cluster themselves around some average value. In
CTT, this value is known as the true score .
In IRT however, the definition of a true score according to D.N. Lawley is used. The formula
for a true score is as shown below:
N
TS j = ∑ Pi (θ j )
i =1
Where TSj is the true score for examinee with ability θj
i is an item
Pi(θj) depends upon the particular ICC model employed
In order to calculate the true scores of these test takers at a given ability level, we assume an
ability of b=+1 and let us find the probability of this test taker of ability=+1 for a correct
response using BIRT software.
1. For the first item, b=1.5, a=1.42. For an ability of +1 the probability of getting the
correct answer from BIRT software can be read as follows:
55
According to the table given above, Pi(θ) at θ =+1 is 0.330. The calculation for the same is
given below:
Pi (θ ) =
1
1 + e − a*(θ −b )
=
1
1 + e −1.42*(1−1.5)
1
=
= 0.329
1 + e0.71
2. For the second item, b=0.42, a=1.42. For an ability of +1 the probability of getting the
correct answer is as shown below:
given below:
Pi (θ ) =
1
1 + e − a*(θ −b )
=
1
1 + e −1.42*(1−0.42)
=
1
= 0.695
−0.82
1+ e
56
3. For the third item, b=2.29, a=1.42. For an ability of +1 the probability of getting the
given below:
Pi (θ ) =
1
1 + e − a*(θ −b )
=
1
1 + e −1.42*(1−2.29)
=
1
= 0.138
1.83
1+ e
4. For the forth item, b=0.92, a=1.42. For an ability of +1 the probability of getting the
57
given below:
Pi (θ ) =
1
1 + e − a*(θ −b )
=
1
1 + e −1.42*(1−0.92)
=
1
= 0.528
−0.11
1+ e
5. For the fifth item, b=-0.28, a=1.42. For an ability of +1 the probability of getting the
58
given below:
Pi (θ ) =
1
1 + e − a*(θ −b )
=
1
1 + e −1.42*(1+0.28)
=
1
= 0.860
−1.81
1+ e
Thus, test score of a test taker of ability=1 is obtained. The test taker score at this ability
for all the five items is the sum of all the individual Pi(θ) as sown below:
= 0.329+0.695+0.138+0.528+0.860 = 2.551
Thus, for a test taker of ability=1 the true score for the test is 2.55. Similarly, we may obtain
the test scores at all ability levels from -3 to +3 as indicated in the table below:
Ability
Level
Item1
Item2
Item3
Item4
Item5
Total
-3
-2
-1
0
+1
+2
0.002
0.007
0.028
0.106
0.330
0.670
0.008
0.031
0.117
0.355
0.695
0.904
0.001
0.002
0.009
0.037
0.138
0.398
0.004
0.016
0.061
0.213
0.528
0.823
0.021
0.080
0.265
0.598
0.860
0.962
0.036
0.136
0.48
1.309
2.551
3.757
+3
0.894
0.974
0.733
0.950
0.991
4.542
The table below shows the ability levels and the total Pi(θ) of all these ability levels added up.
A plot of ability along the X-axis and test score along the Y-axis for each of these test takers of
ability ranging from -3 to +3 will generate a test characteristic curve as shown below:
59
Ability
Level
Total
-3
-2
-1
0
+1
+2
+3
0.036
0.136
0.48
1.309
2.551
3.757
4.542
Figure: Items response function and test response function for five items
The procedure used to work out the test characteristic curve for Two Parameter model can be
similarly used to work out the curves for the Single and Three Parameter models.
An important concept for the test characteristic curve is that it concerns a particular test and
the test characteristic curves for different tests would be different.
When a Single or Two Parameter model is used for N items in a test, the left tail of the test
characteristic curve approaches zero as the ability score approaches negative infinity; its upper
tail approaches the number of items in the test as the ability score approaches positive infinity.
The implication of this is that under these two models, a true score of zero corresponds to an
ability score of negative infinity, and a true score of N corresponds to an ability level of
positive infinity. When a Three Parameter model is used for N items in a test, the lower tail of
the test characteristic curve approaches the sum of the guessing parameters for the test items
rather than zero. This reflects the fact that under this model, very low-ability test takers can
get a test score simply by guessing. The upper tail of the test characteristic curve still
approaches the number of items in the test. Hence, a true score of N corresponds to an ability
of positive infinity under all the three ICC models.
The primary role of the test characteristic curve in IRT is to provide a means of transforming
ability scores to true scores. This becomes of interest in practical situations where the user of
the test may not be able to interpret an ability score. By transforming the ability score into a
true score, the user is given a number that relates to the number of items in the test. This
number is in a more familiar frame of reference and the user is able to interpret it. However,
those familiar with IRT can interpret the ability score directly. The test characteristic curve also
plays an important role in the procedures for equating tests.
60
The general form of the test characteristic curve is that of a monotonically increasing function.
In some cases, it has a rather smooth S-shape similar to an ICC. In other cases, it will increase
smoothly, and then have a small plateau before increasing again. However, in all cases, it will
be asymptotic to a value of N in the upper tail. The shape of the test characteristic curve
depends upon a number of factors, including the number of items, the ICC model employed,
and the values of the item parameters.
Test Information Function
The test information function is an extremely useful feature of IRT. It indicates how well the
test is doing in estimating ability over the whole range of ability scores. Since a test is used to
estimate the ability of a test taker, the amount of information yielded by the test at any ability
level can also be obtained. A test is a set of items; therefore, the test information at a given
ability level is simply the sum of the item information at that level.
Since the test information is obtained by summing the item information at a given ability level,
the amount of information is defined at the item level. Consequently, the test information
function is defined as shown below:
N
I (θ ) = ∑ I i (θ )
i =1
Where I(θ)is the amount of test information at any ability level θ
Ii(θ) is the amount of information for item I at any ability level θ
N is the number of items in a test
The most important thing about the test information function is that it predicts the accuracy to
which we can measure any value of the latent ability. The general level of the test information
function will be much higher than that for a single item information function. Thus, a test
measures ability more precisely than does a single item. Hence, more the items in a test,
greater the amount of information. Longer tests will measure a test taker’s ability with greater
precision than will shorter tests. Plotting the amount of test information against ability yields a
graph of the test information function for a ten-item test as shown below:
61
Figure: A test information function
Note: The Y-axis in the above graph should be read as 0 to 5 instead of 0 to 10.
The maximum value of the test information function as seen above is modest and the amount
of information decreases rather steadily as the ability level differs from that corresponding to
the maximum. Thus, ability is estimated with some precision near the center of the ability
scale. However, as the ability level approaches the extremes of the scale, the amount of test
information decreases significantly.
While the ideal test information function often may be a horizontal line, it may not be the best
for a specific purpose. For example, if we were interested in constructing a test to award
scholarships, this ideal might not be optimal. In this situation, we should measure ability with
considerable precision at ability levels near the ability used to separate those who will receive
the scholarship from those who do not. The best test information function in this case would
have a peak at the cutoff score. Other specialized uses of tests could require other forms of
the test information function. While an information function can be obtained for each item in a
test, this is rarely done. The amount of information yielded by each item is rather small, and
we typically do not attempt to estimate a test taker’s ability with a single item. Consequently,
the amount of test information at an ability level and the test information function are of
primary interest.
The mathematical definition of the amount of item information depends upon the particular
ICC model employed. Therefore, it is necessary to examine these definitions under each
model.
Let us look into a test of five items administered on ten test takers, analyzed through a Two
Parameter model. The item parameters values are as shown below:
62
Item
b
a
1
2
3
4
5
1.5
0.42
2.29
0.92
-0.28
1.42
1.42
1.42
1.42
1.42
The amount of item information and the test information will be computed for the same seven
ability levels as shown below:
1. For the first item, b=1.5, a=1.42. For an ability of +1, Pi(θ) is 0.330 as calculated in the
example for item information. Thus, the Ii(θ) will be calculated as shown below:
Pi (θ ) = 0.330
Qi (θ ) = 1 − Pi (θ ) = 1 − 0.330 = 0.670
I i (θ ) = a 2 * Pi (θ ) * Qi (θ ) = 1.42 *1.42 * 0.330 * 0.670
I i (θ ) = 0.445
2. For the second item, b=0.42, a=1.42. For an ability of +1, Pi(θ) is 0.695 as calculated
in the example for item information. Thus, the Ii(θ) will be calculated as shown below:
Pi (θ ) = 0.695
Qi (θ ) = 1 − Pi (θ ) = 1 − 0.695 = 0.305
I i (θ ) = a 2 * Pi (θ ) * Qi (θ ) = 1.42*1.42*0.695*0.305
I i (θ ) = 0.427
3. For the third item, b=2.29, a=1.42. For an ability of +1, Pi(θ) is 0.138 as calculated in
the example for item information. Thus, the Ii(θ) will be calculated as shown below:
63
Pi (θ ) = 0.138
Qi (θ ) = 1 − Pi (θ ) = 1 − 0.138 = 0.862
I i (θ ) = a 2 * Pi (θ ) * Qi (θ ) = 1.42 *1.42 * 0.138* 0.862
I i (θ ) = 0.239
4. For the fourth b=0.9, a=1.42. For an ability of +1, Pi(θ) is 0.528 as calculated in the
Pi (θ ) = 0.528
Qi (θ ) = 1 − Pi (θ ) = 1 − 0.528 = 0.427
I i (θ ) = a 2 * Pi (θ ) * Qi (θ ) = 1.42 *1.42 * 0.528* 0.427
I i (θ ) = 0.502
5. For the fifth, b=-0.28, a=1.42. For an ability of +1, Pi(θ) is 0.860 as calculated in the
Pi (θ ) = 0.860
Qi (θ ) = 1 − Pi (θ ) = 1 − 0.860 = 0.140
I i (θ ) = a 2 * Pi (θ ) * Qi (θ ) = 1.42 *1.42 * 0.860 * 0.140
I i (θ ) = 0.242
The Pi(θ) and Qi(θ) values for all the five items are calculated as shown in the table below:
64
Ability
Item1
Item2
Item3
Level P Q=1-P P Q=1-P P Q=1-P
-3
-2
-1
0
+1
+2
+3
0.00
2
0.00
7
0.02
8
0.10
6
0.33
0
0.67
0
0.89
4
P
Item4
Q=1-P
P
Item5
Q=1-P
0.998
0.008
0.992
0.001
0.999
0.004
0.996
0.021
0.979
0.993
0.031
0.969
0.002
0.998
0.016
0.984
0.080
0.920
0.972
0.117
0.883
0.009
0.991
0.061
0.939
0.265
0.835
0.894
0.355
0.645
0.037
0.963
0.213
0.787
0.598
0.402
0.670
0.695
0.305
0.138
0.862
0.528
0.472
0.860
0.14
0.330
0.904
0.196
0.398
0.602
0.823
0.167
0.962
0.038
0.106
0.974
0.026
0.733
0.267
0.950
0.05
0.991
0.009
The Ii(θ) values for all the five items are calculated. The test information at any ability level is
the sum of all Ii(θ) values at that level for all the five items as shown in the table below:
Ability
Level
Item1
a2PQ =
I(θ)
Item2
a2PQ =
I(θ)
Item3
a2PQ =
I(θ)
Item4
a2PQ =
I(θ)
Item5
a2PQ =
I(θ)
Test
Information
Function
-3
0.004
0.016
0.002
0.008
0.0415
0.07153
-2
0.014
0.0606
0.004
0.0317
0.1484
0.258765
-1
0.055
0.2083
0.018
0.1155
0.4462
0.842855
0
0.191
0.4617
0.0718
0.338
0.4847
1.547379
+1
0.446
0.4274
0.2399
0.5025
0.2428
1.858409
+2
0.446
0.3573
0.4831
0.2771
0.0737
1.637069
+3
0.191
0.0511
0.3946
0.0958
0.018
0.75054
The table below gives ability levels and the test information function at each of these levels. A
plot of ability against test information function is shown below. It may be observed that test
information curve is the sum of item information curves of the five items as indicated below:
65
Ability
Level
Test
Information
Function
-3
-2
-1
0
+1
+2
+3
0.07153
0.258765
0.842855
1.547379
1.858409
1.637069
0.75054
Figure: Item information function and test information function of five items
Interpreting the test information function
While the shape of the desired test information function depends upon the purpose for which
a test is designed, some general interpretations can be made. A test information function that
is peaked at some point on the ability scale, measures ability with unequal precision, along the
ability scale. Such a test would be best for estimating the ability of test taker whose abilities
fall near the peak of the test information function. In some tests, the test information function
is rather flat over some region of the ability scale. Such tests estimate some range of ability
scores with nearly equal precision and outside this range with less precision. Thus, the test
would be a desirable one for those test takers whose ability falls in the given range. When
interpreting a test information function, it is important to keep in mind the reciprocal
relationship between the amount of information and the variability of the ability estimates. To
translate the amount of information into a standard error of estimation, we need to take the
reciprocal of the square root of the amount of test information as shown below:
S .E (θ ) =
1
I (θ )
Test Information Function of Single Parameter Model
The test information function relates to the item information function in a way that it is equal
to the sum of item information functions. The test information under Single Parameter model
is shown below:
66
I j (θ j ) = ∑ i I ij (θ j , bi )
Figure: Item information functions and test information function for five items
In the above graph, although the test information function is plotted on the same scale as the
item information functions, a separate axis is added to emphasize the difference. The test as a
whole is far more informative than each item alone, and it spreads the information over a
wider ability range. The information provided by each item is, in contrast, concentrated around
ability levels that are close to its difficulty.
Using BILOG-MG 3.0, test information curve is obtained as:
67
Subtest: TEST0001
0.6
2.16
0.5
1.72
0.4
Information
0.3
Standard Error
1.29
0.86
0.2
0.43
0.1
0
-3
-2
-1
0
1
2
3
0
S cale S cor e
Test infor m ation cur ve: solid line
S tandar d er r or cur ve: dotted line
The total test information for a specific scale score is read from the left vertical axis.
The standard error for a specific scale score is read from the right vertical axis.
Test Information Function of Two Parameter Model
The formula for the test information function under Two Parameter model is shown below:
Ij (θj) = Σi Iij (θj , bi , ai) = Σi a2i P(θ , bi , ai) * Q(θ , bi , ai)
Because the item information functions in the Two Parameter model depend so strongly on
the discrimination parameters ai, the shape of the test information function can become rather
curvy and unpredictable—especially in tests with very few items like our examples. In practice,
we should have a test information function that is high and reasonably smooth over the
relevant ability range — say, (-3; +3). This could be ideally attained with a large number of
items having large discrimination parameters and difficulties evenly distributed over the ability
range. Items with very low discrimination parameters are usually discarded from practical use.
68
Subtest: TEST0001
0.6
2.16
0.5
1.72
0.4
Information
0.3
Standard Error
1.29
0.86
0.2
0.43
0.1
0
-3
-2
-1
0
1
2
3
0
S cale S cor e
Test Information Function of Three Parameter Model
The test information function of the Three Parameter model is the sum of the item information
functions over the items in a test. The formula for the test information function of Three
Parameter model is shown below:
Q (θ ) [ P (θ ) − c]2
I j (θ j ) = ∑ i I ij (θ j , bi , ai , ci ) = ∑ i a
P (θ ) (1 − c)
2
As seen earlier that the item information function depends strongly on the discrimination
parameters ai. In the Three Parameter model, there is the additional influence of the ‘guessing
parameters’ ci. Larger ci decrease the item information and shift its maximum away from bi. In
practical applications, we should have a test information function that is high and reasonably
smooth over the relevant ability range — say, (-3; +3).
69
Subtest: TEST0001
0.6
2.16
0.5
1.72
0.4
Information
0.3
Standard Error
1.29
0.86
0.2
0.43
0.1
0
-3
-2
-1
0
1
2
3
0
S cale S cor e
Estimating Parameters
As seen earlier the ability and item parameters were assumed known and hence it was easy to
plot, examine and modify the IRF. If the item parameters are known then the ability can be
estimated easily. Alternatively, the estimation of item parameters will become easy if the true
abilities of the test takers were known.
Since the actual values of the item parameters in a test are unknown, one of the important
tasks to be performed when a test is analyzed under IRT is to estimate these parameters. The
estimates thus obtained yield information about the technical properties of the test items. For
understanding estimation, an individual item is taken and item difficulty, item discrimination,
item guessing parameters for this item will be estimated wherever relevant in the three
models.
Procedure for Estimating Parameters
70
Let us look into the case of a typical test. This test of N number of items is administered to M
number of test takers. The ability scores of these test takers will be distributed over a range of
ability levels on the ability scale. These test takers are divided into J number of groups along
the scale so that all the test takers within a given group have the same ability level θj and
there will be mj test takers within group j, where j = 1, 2, 3. . . . J. Within a particular ability
score group, rj test takers answer the given item correctly. Thus, at an ability level of θj, the
observed proportion of correct response is p(θj) = rj/mj , which is an estimate of the
probability of correct response at that ability level. Now the value of rj can be obtained and
p(θj) computed for each of the j ability levels established along the ability scale. If the
observed proportions of correct response in each ability group are plotted, the result will be
something like that shown in Figure 3-1:
The next task is to find the ICC that best fits the observed proportions of correct response. To
do so, a model needs to be selected for the curve to be fitted. Although any of the three
models could be used, the two-parameter model is employed here. The procedure used to fit
the curve is based upon maximum likelihood estimation. Under this approach, initial values for
the item parameters, such as b=0.0, a=1.0, are established a priori. Then, using these
estimates, the value of P(θj) is computed at each ability level via the equation for the ICC
model. The agreement of the observed value of p(θj) and computed value P(θj) is determined
across all ability groups. Then, adjustments to the estimated item parameters are found, that
result in better agreement between the ICC defined by the estimated values of the parameters
and the observed proportions of correct response. This process of adjusting the estimates is
continued until the adjustments get so small that little improvement in the agreement is
possible. At this point, the estimation procedure is terminated and the current values of b and
a are the item parameter estimates. Given these values, the equation for the ICC is used to
71
compute the probability of correct response P(θj) at each ability level and the ICC can be
plotted. The resulting curve is the ICC that best fits the response data for that item. Figure 3-2
shows an ICC fitted to the observed proportions of correct response shown in Figure 3-1. The
estimated values of the item parameters were b = -.37 and a = 1.25.
An important consideration within IRT is whether a particular ICC model fits the item response
data for an item. The agreement of the observed proportions of correct response and those
yielded by the fitted ICC for an item is measured by the chi-square goodness-of-fit index. This
index is defined as follows:
J
[ p (θ j ) − P (θ j )]2
j =1
P (θ j ) * Q(θ j )
X 2 = ∑ mj
Where J is the number of ability groups.
θj is the ability level of group j.
mj is the number of examinees having ability θj.
p(θj) is the observed proportion of correct response for group
j.
P(θj) is the probability of correct response for group j computed from the ICC model using the
item parameter estimates.
72
If the value of the obtained index is greater than a criterion value, the ICC specified by the
values of the item parameter estimates does not fit the data. This can be caused by two
things. First, the wrong ICC model may have been employed. Second, the values of the
observed proportions of correct response are so widely scattered that a good fit, regardless of
model, cannot be obtained. In most tests, a few items will yield large values of the chi-square
index due to the second reason. However, if many items fail to yield well-fitting ICCs there
may be reason to suspect that the wrong model has been employed. In such cases, reanalyzing the test under an alternative model, say the Three Parameter model rather than a
Single Parameter model, may yield better results. In the case of the item shown in Figure 3-2,
the obtained value of the chi-square index was 28.88 and the criterion value was 45.91. Thus,
the Two Parameter model with b=-.37 and a=1.25 was a good fit to the observed proportions
of correct response. Unfortunately, not all of the test analysis computer programs provide
goodness-of-fit indices for each item in the test.
The actual maximum likelihood estimation (MLE) procedure is rather complex mathematically
and entails very laborious computations that must be performed for every item in a test. In
fact, until computers became widely available, IRT was not practical because of its heavy
computational demands. For present purposes, it is not necessary to go into the details of this
procedure. It is sufficient to know that the curve-fitting procedure exists, that it involves a lot
of computing, and that the goodness-of-fit of the obtained ICC can be measured. Because test
analysis is done by computer, the computational demands of the item parameter estimation
process do not present a major problem today.
Examples
1. Let’s look at an illustrative numerical example for item parameter estimation. The model
used for this example is Rasch’s Single Parameter model for easy purpose of illustration
and easy understanding. Therefore, a single parameter namely item difficulty is to be
estimated.
Let us take an example of an objective type test of 20 items given on 76 test takers.
The following table illustrates the data of number right
scores and the number of
test takers obtaining every score:
Number Right
Score
Number of Test Takers Obtaining
This Score
18
17
16
15
14
13
4
4
5
12
7
10
73
12
11
10
9
8
7
6
8
11
5
6
2
1
1
Descriptive Statistics of Number Right Scores of 76 Test Takers for 20 Items
Case Processing Summary
Cases
Missing
N
Percent
0
.0%
Valid
N
VAR00001
76
Percent
100.0%
Total
N
76
Percent
100.0%
Descriptives
VAR00001
Mean
95% Confidence
Interval for Mean
Lower Bound
Upper Bound
5% Trimmed Mean
Median
Variance
Std. Deviation
Minimum
Maximum
Range
Interquartile Range
Skewness
Kurtosis
Statistic
12.8684
12.2271
Std. Error
.3219
13.5097
12.8977
13.0000
7.876
2.8064
6.00
18.00
12.00
4.0000
-.122
-.554
.276
.545
VAR00001
VAR00001 Stem-and-Leaf Plot
Frequency
.00
2.00
8.00
16.00
18.00
19.00
9.00
4.00
Stem &
0
0
0
1
1
1
1
1
.
.
.
.
.
.
.
.
Leaf
67
88999999
0000011111111111
222222223333333333
4444444555555555555
666667777
8888
74
Stem width:
Each leaf:
10.00
1 case(s)
Let us look at the 5th item for purpose of parameter estimation. The correct answer to this
item is B. The various responses of the above groups of test takers are given below:
Number
Right Score
Number of Test
Takers Obtaining
This Score
Number Scoring
Right Answer
Proportion of
Right Answers
(Probability)
18
17
16
15
14
13
12
11
10
9
8
7
6
4
4
5
12
7
10
8
11
5
6
2
1
1
4
4
2
5
1
6
2
1
1
0
1
1
0
4/4=1.0
4/4=1.0
2/5=0.4
5/12=0.41
1/7=0.14
6/10=0.6
2/8=0.25
1/11=0.09
1/5=0.2
0/6=0
½=0.5
1/1=1
0/1=0
For the proportion of right answers and number right score groups given above,
graph is plotted with an approximate ICC as shown below:
a
Graph: ICC – Proportion of Right Answers/Number Right Score
75
A rough graphical representation of the proportion of right answers at every number right
score plotted against the number right score is obtained by trial and error method in curve
fitting. The rough representation is given in the graph. It can be seen that the curve’s point
of contraflexure is seen at a number right score of 15 corresponding to a rough
estimate of 15 number right score and corresponding +1.5 on the ability scale as indicated in
the graph.
Let us assume the first estimate of item difficulty b, of these items to be 1.5. For a
single parameter b=1.5, the ICC or IRF is obtained by using BIRT software as shown below:
76
The BIRT curve proportions of Pi(θ) at all value from -3 to +3 can be compared now with the
obtained proportions of right answers at the number right score levels at the corresponding
assumed ability levels as shown in the table below:
Number
Observed
Ability
Pi(0) at this
77
Right Score
proportion of
right answers
at this score
levels
level
18
17
16
15
14
13
12
11
10
9
8
7
6
1.0
1.0
0.4
0.41
0.14
0.6
0.25
0.09
0.2
0
0.5
1
+3
+2.5
+2
+1.5
+1
0.5
0
-0.5
-1
-1.5
-2
-2.5
-3
0.894
0.805
0.67
0.5
0.33
0.195
0.106
0.055
0.028
0.014
0.007
0.003
0
Benjamin Wright’s Mathematical Formulation of Rasch Model
Steps:
1. Number of persons who got ith item right. i=1 to 5
i=1 n1=6
i=2 n2=3
i=3 n3=3
i=4 n4=2
i=5 n5=5
2. Number of persons who got ith item wrong. I=1 to 5
i=1 n1=3
i=2 n2=6
i=3 n3=6
i=4 n4=7
i=5 n5=4
3.
1.
2.
3.
4.
5.
Calculate log ratio of wrong to right as follows:
ln(3/6)
ln(6/3)
ln(6/3)
ln(7/2)
ln(4/5)
X1=ln(3/6)= - 0.69315
X2=ln(6/3)= + 0.69315
X3=ln(6/3)= + 0.69315
78
X4=ln(7/2)= 1.25276
X5=ln(4/5)= - 0.22314
4. Calculate mean of Xi over L items (here 5) as follows:
5
X= ∑ X i / 5 = 1.72277 / 5 = 0.344554
1
5. Calculate variance of Xi over L items as follows:
2
U= ∑ ( X − X i ) / L − 1
Xi
X1=
-0.69315
X2=
0.69315
X3=
0.69315
X4=
1.25276
X5=
-0.22314
(X- Xi)
(X- Xi)2
[0.34455-(-0.69315)]
(-1.03770)2
1.07682
[0.34455-0.69315]
(-0.34860)2
0.12152
[0.34455-0.69315]
(-0.34860)2
0.12152
[0.34455-1.25276]
(-0.9082)2
-0.82482
[0.34455-(-0.22314)]
(0.56769)2
0.32227
Sum=
2.46697
U=2.46697/4=0.616745
6. Calculate Nr as the number of persons who got r items right for r=1 to r=4.
1 item right - 3 persons
2 items right - 3 persons
3 items right - 2 persons
4 items right - 1 person
7. Calculate the log ratio of right to wrong answers over L items as follows:
Yr=ln(r/L-r)
Y1=ln(3/5-3)=ln(3/2)=
Y2=ln(3/5-3)=ln(3/2)=
Y3=ln(2/5-2)=ln(2/3)=
Y4=ln(1/5-1)=ln(1/4)=
0.405465
0.405465
-0.405465
-1.38629
8. Calculate the mean Y of Yr over N persons as follows:
79
Y= ∑ N r Yr / N
Nr
N1=3
N2=3
N3=2
N4=1
Yr
Y1= 0.405465
Y2= 0.405465
Y3= -0.405465
Y4= -1.38629
NrYr
1.216395
1.216395
-0.81093
-1.38629
Sum = 0.23557
Y=0.23557/4=0.058893
9. Calculate the variance of Yr.
∑N
V=
r
(Yr − Y ) 2
( N − 1)
N-1=4
N1(Y1 - Y)2 + N2(Y2 - Y)2 + N3(Y3 - Y)2 + N4(Y4 - Y)2 = 0.239531
10. Calculate the expansion factor due to variation in item difficulty as follows:
Ed=
[1 + (U / 2.89)]
= 1.235261
[1 − (VU / 8.35)]
11. Calculate the expansion factor due to variation in person ability as follows:
Ea=
[1 + (V / 2.89)]
= 1.102386
[1 − (VU / 8.35)]
12. Calculate the difficulty of item i as follows:
Di= E a ( X i − E d )
80
Item No.
1
2
3
4
5
Difficulty Di
-2.12585
-0.59762
-0.59762
0.019294
-1.60773
Remark
Easiest item
Most difficulty item
13. Plot ICC for each of these items using Rasch Model.
Item Difficulty =b
Pi(θ)=
1
1 + e − (θ
−b)
Vary θ as -3.00, -2.95, ………………… 2.95, 3.00
b=-2.12585
θ
(θ-b)
e
− (θ − b )
+ 0 .8 7 4 1 5
-3.0
[-3.0(-2.12585)]
e
-2.95
[-2.95(-2.12585)]
e +0.82415
=2.3968
=2.2799
1+ e
− (θ − b )
1/(1+ e
− (θ − b )
)
Pi
1+2.3968=
3.3968
1/3.3968
0.294392
1+2.2799=
3.2799
1/3.2799
0.30488
And so on..
Assume b=-2.13
θ
(θ-b)
e
− (θ − b )
1+ e
− (θ − b )
1/(1+ e
− (θ − b )
)
Pi
-3.0
[-3.0(-2.13)]
e + 0 .8 7
=
1+2.3869=
3.3869
1/3.3869
0.295254
-2.95
[-2.95(-2.13)]
e +0.82 =
2.2705
1+2.2705=
3.2705
1/3.2705
0.305764
-2.0
[-2.0(-2.13)]
e −0.13 =
1+0.8780=
1.8780
1/1.8780
0.532454
2.3869
81
0.8780
-1.0
[-1.0(-2.13)]
e −1.13 =
0
[0(-2.13)]
e −2.13 =
+1.0
[1.0(-2.13)]
e −3.13 =
+2.0
[2.0(-2.13)]
e −4.13 =
+3.0
[3.0(-2.13)]
e −5.13 =
0.3230
0.1188
0.0437
0.0160
0.0059
1+0.3230=
1.3230
1/1.3230
0.755839
1+0.1188=
1.1188
1/1.1188
0.893785
1+0.0437=
1.0437
1/1.0437
0.958113
1+0.0160=
1.0160
1/1.0160
0.984172
1+0.0059=
1.0059
1/1.0059
0.994118
14. Similarly, draw ICCs for items 2, 3, 4 & 5.
15. Alternatively, use BILOG. Responses and correct responses of 10 test takers for 5 items.
•
•
•
Rasch’s Single Parameter model
Birnbaum’s Two Parameter model
FredLord’s Three Parameter model
Taking the eighth item and using the number right scores of 22, 21, ………………. 6 the number
of test takers obtaining each score and amongst them the number who got the eighth item
right, can be ascertained. The data for the same is given below:
SCORE
HAG
22
21
20
19
18
17
16
15
CORRES
ZSCORE
3.338509
3.02795
2.717391
2.406832
2.096273
1.785714
1.475155
1.164596
NUMBER
GETTING THIS
SCORE
2
3
10
24
40
79
151
185
NUMBER
GETTING THIS
QN. RIGHT
2
3
10
22
36
72
141
171
PROPORTION
GETTING THE
RIGHT ANSWER
1
1
1
0.916666667
0.9
0.911392405
0.933774834
0.924324324
82
LAG
14
13
9
8
7
6
5
4
3
2
1
0.854037
0.543478
-0.69876
-1.00932
-1.31988
-1.63043
-1.94099
-2.25155
-2.56211
-2.87267
-3.18323
309
90
228
276
160
98
71
27
22
10
3
264
78
138
162
76
45
23
5
1
0
0
0.854368932
0.866666667
0.605263158
0.586956522
0.475
0.459183673
0.323943662
0.185185185
0.045454545
0
0
Interpretation of the Best Curve Fit to Q.8 using HAG and LAG to determine
its Item Difficulty
If we try to find the best fit for the statistics of Q.8 provided by the data, we get the model as
MMF model which is:
Y=(a*b+c*xd)/(b+xd)
Where a=-.0015206493, b=144.46167, c=1.04367, d=2.5051428
X=total scores achieved by test takers and y=proportion of test takers getting Q.8 right when
their score is x.
Checking the model at x=22, we get y=0.981023, which is very close to the actual value.
Hence it can be concluded that the model is very accurate.
The correlation coefficient is 0.9986173 and the standard error is 0.0195901. Also checking
against y=0.5 we get x=7.04913. The corresponding Z score is
–1.3046, which denotes the
item difficulty of Q.8.
Interpretation of the Inverse Exponential Curve Fit to Q.8 to determine its
Item Difficulty
If we try to fit exponential model to the statistics of Q.8 provided by the data, we get the
model as follows:
Y=a*(1-exp(-b*x))
83
Where a=1.53636, b=0.0528
X=total scores achieved by test takers and y=proportion of test takers getting Q.8 right when
their score is x.
Checking the model at x=22, we get y=1.055, which is very close to the actual value but still it
is not as close as the previous model. Hence it can be concluded that the model is moderately
accurate.
The correlation coefficient is 0.991 and the standard error is 0.05514. Also checking against
y=0.5 we get x=7.45586. The corresponding Z score is -1.1783 which denotes the item
difficulty of Q.8.
Note: The number right scores have also been converted into Z scores and the proportion of
right answers for eighth item at each of these scores is also given in the table.
A plot of this is attempted through Curve Expert software and the best fit (MMF Model) is
arrived at. From this graph reading at 0.5 the difficulty of this item is estimated. Note that this
is on a different metric scale.
Group Invariance of Item Parameters
84
The group invariance of the item parameters is a very powerful feature of IRT. It says that the
values of the item parameters are a property of the item, not of the group that responded to
the item. These item parameters can be estimated from any segment of the item response
curve. This means that these parameters can be estimated from any group of test takers. The
term group invariance refers to this independence of the item parameter estimates from the
distribution of ability. Thus, the item parameters are known to be group invariant.
Unlike IRT, under CTT the item difficulty is the overall proportion of incorrect response to an
item for a group of test takers. Thus, if an item with b=0 were responded to by a low-ability
group, few of the test takers would get it correct. The item difficulty index under CTT would
yield a low value say 0.3, as the item difficulty for this group. If the same item were
responded to by a high ability group, most of the test takers would get it correct. The item
difficulty index under CTT would yield a high value, say 0.8, indicating that the item was easy
for this group. Thus, the value of the item difficulty index under CTT is not group invariant.
Because of this, item difficulty as defined under IRT is easier to interpret because it has a
consistent meaning that is independent of the group used to obtain its value.
Note:
Even though the item parameters are group invariant, this does not mean that the numerical
values of the item parameter estimates yielded by the maximum likelihood estimation
procedure for two groups of test takers taking the same items will always be identical. The
obtained numerical values will be subject to variation due to sample size, how well-structured
the data is, and the goodness-of-fit of the curve to the data. In addition, the item must be
used to measure the same latent trait for both groups. An item’s parameters do not retain
group invariance when taken out of context, i.e., when used to measure a different latent trait
or with test takers from a population for which the test is inappropriate.
Examples
1. Let us assume that two groups of test takers are chosen from a population of test
takers. The first group has a range of ability scores from -3 to -1, with a mean of -2.
The second group has a range of ability scores from +1 to +3 with a mean of +2. The
observed proportion of correct response to a given item is computed from the item
response data for every ability level within each of the two groups. These proportions of
correct response are plotted as shown below:
85
Figure 3-3: Observed proportions of correct response for group 1
The maximum likelihood procedure is then used to fit an ICC to the data and
numerical values of the item parameter estimates, b(1)=-.39 and a(1)=1.27, were
obtained [b(1) indicates the value of b for group 1 and a(1) indicates the value of a for group
1]. The ICC defined by these estimates is then plotted over the range of ability encompassed
by the first group as shown below:
Figure 3-4: The ICC fitted to group 1 data
86
The process is repeated for the second group. The observed proportions of
response for group 2 are shown below:
correct
Figure 3-5: Observed proportions of correct response for group 2
The maximum likelihood procedure is then used to fit an ICC to the data and
numerical values of the item parameter estimates, b(2)=-.39 and a(2)=1.27, were obtained
[b(1) indicates the value of b for group 1 and a(1) indicates the value of a for group 1]. The
ICC defined by these estimates is then plotted over the range of ability encompassed by the
second group as shown below:
87
Figure 3-6: The ICC fitted to group 2 data
An important point of observation here is that, under these conditions when b(1)=b(2)
and a(1)=a(2), the two groups yield the same values of the item parameters. Hence, the item
parameters are group invariant.
While this result may seem a bit unusual, its validity can be demonstrated easily
by
considering the process used to fit an ICC to the observed proportions of correct response.
Since the first group had a low average ability (-2), the ability levels spanned by group 1 will
encompass only a section of the curve, in this case, the lower left tail of the curve.
Consequently, the observed proportions of correct response will range from very small
to moderate values. When fitting a curve to this data, only the lower tail of the ICC is
involved. Let us see Figure 3-3 for an example. Since group 2 had a high average ability (+2),
it’s observed proportions of correct response range from moderate to very near 1. When fitting
an ICC to this data, only the upper right-hand tail of the curve is involved, as shown in Figure
3-6. Since the same item was administered to both groups, the two curve-fitting processes
were dealing with the same underlying ICC. Consequently, the item parameters yielded by the
two analyses should be the same. The output shown below integrates the two groups into a
single representation showing how the same ICC fits the two sets of proportions of correct
response:
Figure 3-7: The ICC fitted to the pooled data, b=-0.39 and a=1.27
2. Let us illustrate the use of BIRT software to prove group invariance. We are choosing
upper bound and lower bound groups, upper bound from +3 to +1 and lower bound
88
from -1 to -3. Separate ICCs are drawn for these two groups and then a combined ICC
is also shown:
The output shown below indicates the Lower Bound and Upper Bound values for the
two groups of abilities:
The output shown below indicates the plots of the lower bound group of
abilities:
89
The output shown below indicates the plots of the upper bound group of abilities:
The output shown below indicates the ICC of the item for lower bound group of
abilities:
90
The output shown below indicates the ICC of the item for upper bound group of
abilities:
The output shown below indicates the combined ICC of the item for the two groups of
abilities (item has same item difficulty for the two groups of abilities):
91
It is observed that the individual ICCs and the combined ICC give rise to the same b values.
For a sample of 25 items administered on 1000 test takers, item #5 has been taken to
illustrate group invariance. Three methods are followed and they are as follows:
1. Higher Ability Group (HAG) of top 27% and Lower Ability Group (LAG) of bottom 27%
of the total group are considered as two groups. For item #5 the proportion of right
answers of score sets in HAG and LAG are taken out and the same are given below:
HAG
LAG
SCORE
CORRES
ZSCORE
NUMBER
GETTING
THIS
SCORE
22
21
20
19
18
17
16
15
14
13
9
3.338509
3.02795
2.717391
2.406832
2.096273
1.785714
1.475155
1.164596
0.854037
0.543478
-0.69876
2
3
10
24
40
79
151
185
309
90
228
NO. OF
PEOPLE
GETTING
THIS QN.
RIGHT
2
3
8
20
33
60
116
123
196
59
96
PROPORTION
GETTING THE
RIGHT ANSWER
1
1
0.8
0.833333333
0.825
0.759493671
0.768211921
0.664864865
0.634304207
0.655555556
0.421052632
92
8
7
6
5
4
3
2
1
-1.00932
-1.31988
-1.63043
-1.94099
-2.25155
-2.56211
-2.87267
-3.18323
276
160
98
71
27
22
10
3
84
56
26
19
4
2
1
0
0.304347826
0.35
0.265306122
0.267605634
0.148148148
0.090909091
0.1
0
Interpretation of the Best Curve Fit to Q.5 to determine Item Difficulty
using HAG and LAG
If we try to find the best fit for the statistics of HAG of Q.5, provided by
get the model as LINEAR model which is:
the data, we
Y=(a+b*x)
Where a=0.10769,b=0.40946
x=total scores achieved by test takers and y=proportion of test takers
right when their score is x.
getting
Q.5
Checking the model at x=22, we get y=1.00851, which is very close to
value. Hence it can be concluded that the model is very
accurate.
the
actual
The correlation coefficient is 0.92574 and the standard error is 0.10724.
against y=0.5, we get x=9.581.
Also checking
If we try to find the best fit for the statistics of LAG of Q.5, provided by
get the model as LINEAR model which is:
the data, we
Y=(a+b*x)
Where a=-.01833,b=0.04734
getting
Q.5
Checking the model at x=22, we get y=1.02334, which is not very close to the actual
value, but still acceptable. Hence it can be concluded that
the
model
is
moderately
accurate.
93
against y=0.5 we get x=10.9471.
Incidentally, the Z scores for these number right scores are also worked out. A plot of
number right scores in each of the groups and the
proportion of test takers getting
the right answers in the group is plotted
separately for HAG and LAG. Using the Curve
Expert software, the best fit for both are found out. They seem to be in agreement with
the total group of proportions of right answers. At proportion equal to 0.5 (its
taken
to correspond to approximately probability of getting the right answer as 0.5), the
number right score (approximately indicating the ability) in each of these groups is
calculated. These scores compare
very well within limits of standard error, number
right score of the
total group with a proportion of 0.5. These values are 8.81 for the
whole
group, 9.030 for HAG and 9.047 for LAG. The graphs for LAG, HAG and the
whole data are respectively shown below:
94
95
2. The top half and the bottom half of total population of test takers are taken as two
groups following the same procedure. The results and the graphs are shown below:
96
TOP Half
BOTTOM
Half
SCORE
CORRES
ZSCORE
NUMBER
GETTING
THIS SCORE
22
21
20
19
18
17
16
15
14
13
12
3.338509
3.02795
2.717391
2.406832
2.096273
1.785714
1.475155
1.164596
0.854037
0.543478
0.232919
2
3
10
24
40
79
151
185
311
384
384
NUMBER
GETTING
THIS QN.
RIGHT
2
3
8
20
33
60
116
123
196
230
206
11
-0.07764
409
194
0.474327628
10
9
8
7
6
5
4
3
2
1
-0.3882
-0.69876
-1.00932
-1.31988
-1.63043
-1.94099
-2.25155
-2.56211
-2.87267
-3.18323
355
308
276
160
98
71
27
22
10
3
160
119
84
56
26
19
4
2
1
0
0.450704225
0.386363636
0.304347826
0.35
0.265306122
0.267605634
0.148148148
0.090909091
0.1
0
PROPORTION
GETTING THE
RIGHT ANSWER
1
1
0.8
0.833333333
0.825
0.759493671
0.768211921
0.664864865
0.63022508
0.598958333
0.536458333
Interpretation of the Best Curve Fit to Q.5 to determine
Difficulty using Top and Bottom Half Data
Item
If we try to find the best fit for the statistics of TOP half of Q.5 provided
we get the model as LINEAR model which is:
by the data,
Y=(a+b*x)
Where a=0.00523, b=0.04467
x=total scores achieved by test takers and y=proportion of test
getting Q.5 right when their score is x.
accurate.
takers
the
actual
97
If we try to find the best fit for the statistics of BOTTOM half of Q.5
the data, we get the model as LINEAR model which is:
provided
by
Y=(a+b*x)
Where a=-0.01254,b=0.04527
getting Q .5
Checking the model at x=22, we get y=1.05504, which is not very close to the actual
value, still acceptable. Hence it can be concluded that the
model is moderately accurate.
The correlation coefficient is 0.98353 and the standard error is 0.03247.
The graphs for the top and bottom half data are respectively shown
Also checking
below:
98
3. Out of the total population of test takers, those who secure odd-numbered scores and
those who secure even-numbered scores are taken as two distinctive groups. The same
procedure follows for the groups. The values are shown below:
99
EVEN
Scores
ODD
Scores
SCORE
CORRES
Z-SCORE
NUMBER
GETTING
THIS
SCORE
NUMBER
GETTING
THIS QN.
RIGHT
PROPORTION
GETTING THE
RIGHT
ANSWER
6
-1.6304348
98
26
0.265306122
8
10
12
14
16
18
20
22
-1.0093168
-0.3881988
0.23291925
0.85403727
1.47515528
2.09627329
2.7173913
3.33850932
276
355
384
311
151
40
10
2
84
160
206
196
116
33
8
2
0.304347826
0.450704225
0.536458333
0.63022508
0.768211921
0.825
0.8
1
7
-1.3198758
160
56
0.35
9
11
13
15
17
19
21
-0.6987578
-0.0776398
0.54347826
1.16459627
1.78571429
2.4068323
3.02795031
308
409
384
185
79
24
3
119
194
230
123
60
20
3
0.386363636
0.474327628
0.598958333
0.664864865
0.759493671
0.833333333
1
Interpretation of the Best Curve Fit to Q.5 to determine
Difficulty using Even and Odd Data
Item
If we try to find the best fit for the statistics of Q.5, according to even
provided by the data, we get the model as LINEAR model which
is:
scores
Y=a+b*x
Where a=-0.00554, b=0.04472
accurate.
getting Q .5
the
actual
against y=0.5 we get x=11.3027..
100
If we try to find the best fit for the statistics of Q.5, according to odd
scores
provided by the data, we get the model as RATIONAL FUNCTION
model which is:
Y=(a+b*x)/(1+c*x+d*x2)
Where a=0.000305,b=0.06334,c=0.062575,d=-0.00219
accurate.
getting Q .5
the
actual
The graphs for even and odd scores are respectively shown below:
101
Estimating a Test Taker’s Ability
The primary purpose of administering a test to a test taker, under IRT, is to locate the test
taker on the ability scale. By performing this process the test taker can be evaluated in terms
of how much underlying ability he or she possesses. Following this, comparisons among test
takers can be made to assign grades, award scholarships etc. In this chapter we will focus
102
upon the test takers and the procedures for estimating an ability score (parameter) for a test
taker.
The test used to measure an unknown latent trait will consist of N items, each of which
measures some facet of the trait. We have earlier dealt with item parameters and their
estimation and while doing that we assumed that the ability parameter of each test taker was
known. Conversely, to estimate a test taker’s unknown ability parameter, we will assume that
the numerical values of the item parameters are known. A direct consequence of this
assumption is that the metric of the ability scale will be the same as the metric of the known
item parameters.
As seen earlier, when the test is taken, a test taker responds to each of the N items in the
test, and the responses will be dichotomously scored. The result will be a score of either a 1 or
a zero for each item in the test. This set of 1’s and 0’s for the N items is called the test taker’s
item response vector. The item response vector thus obtained and the known item parameters
will then be used to estimate the test taker’s unknown ability parameter.
Ability Estimation Parameters
In IRT maximum likelihood procedures are used to estimate a test taker’s ability. This
procedure is an iterative process as in the case of estimating item parameters. It begins with
some a priori value for the ability of the test taker and the known values of the item
parameters. These are used to compute the probability of correct response to each item for
that test taker. Then an adjustment to the ability estimate is obtained that improves the
agreement of the computed probabilities with the test taker’s item response vector. The
process is repeated until the adjustment becomes small enough that the change in the
estimated ability is negligible. The result is an estimate of the test taker’s ability parameter.
This process is then repeated separately for each test taker taking the test. The estimation
equation is as shown below:
N
∧
∧
θ s +1 = θ s +
∑ a [u
i =1
N
i
i
∧
− Pi (θ s )]
∧
∑ a P (θ
2
i =1
i
∧
s
)Qi (θ s )
Where
^
θs = is the estimated ability of a test taker within iteration s
103
ai = is the discrimination parameter of item i where i=1,2,3……N
ui = is the response made by the test taker to an item i
= 1 for a correct response
= 0 for an incorrect response
^
Pi(θs) = is the probability of a correct response to an item i, under the given
^
ICC model at ability level θ within iteration s
^
^
Qi(θs) = 1 - Pi(θs) is the probability of an incorrect response to an item i,
^
under the given ICC model at ability level θ within iterations
^
Initially, θs on the right hand side of the equal to sign is set to some arbitrary value, such as
1. The probability of correct response to each of the N items in the test is calculated at this
ability level using the known item parameters in the given ICC model. Then the second term to
the right of the equal sign is evaluated. AD, is the adjustment term and the adjusted factor is
^
denoted by
ADθ. The value of θs+1
^
^
on the left side of the equal sign is obtained by adding ADθ to θs. This value θs+1
^
becomes θs in the next iteration. The numerator of the adjustment term contains
^
the essence of the procedure. It should be noted that (ui - Pi(θs)) is the difference between
the test taker’s item response and the probability of correct
^
response at an ability level of θs. As the ability estimate gets closer to the test
^
taker’s ability, the sum of the differences between ui and Pi(θs) gets smaller.
^
Thus, the goal is to find the ability estimate yielding values of Pi(θs) for all items
simultaneously that minimizes this sum. When this happens, the ADθ term
^
becomes as small as possible and the value of θs+1 will not change from
^
104
iteration to iteration. This final value of θs+1 is then used as the test taker’s estimated ability.
The ability estimate will be in the same metric as the numerical values of the item parameters.
A point to be noted here is that the estimation equation given above can be used with all three
ICC models, although the Three Parameter model requires a slight modification.
Let us illustrate the ability estimation process by looking into a test of 5 items administered
under Two Parameter model on 10 test takers. Under this model the known item parameters
are as shown in the table below:
b
a
+1.499
+0.424
+2.292
+0.920
-0.279
1.42
1.42
1.42
1.42
1.42
The test taker’s responses are given in the table below:
Item1 Item2 Item3 Item4 Item5
Test
Taker1
Test
Taker2
Test
Taker3
Test
Taker4
Test
Taker5
Test
Taker6
Test
Taker7
Test
Taker8
Test
Taker9
Test
Taker10
1
1
1
1
1
0
1
1
1
1
1
0
0
1
1
0
0
1
0
0
1
1
0
0
1
1
0
0
0
1
1
0
0
0
0
0
0
1
0
1
1
1
0
0
0
1
0
0
0
0
Let us look at test taker 3. The ui values are given below:
105
Item1 Item2 Item3 Item4 Item5
Test
Taker3
0
ui =0
1
ui=1
0
ui =0
1
ui =1
1
ui =1
^
The a priori estimate of ability for test taker #3 is set to θs=1.0. First iteration is as shown
below:
Next
Estimate
^
a
^
θs
-a(θb)
1.42
1
0
0
1.42
1.42
1
1
1
1.42
1
1
1.42
1
0.71
0.8236
1.8318
0.1136
1.8176
Item
No
b
u
1
1.50
1
2
3
0.42
2.29
4
0.92
0.28
5
p=1/(1+ea(θ-b)
)
q=1-p
a(u-p)
Correction
a *p*q
Factor
2.033991
0.329599
0.670401
0.95197
0.44555
0.438849
6.245118
0.695
0.138024
0.305
0.861976
-0.9869
-0.19599
0.42743
0.2399
0.892615
0.528369
0.471631
0.669715
0.50248
0.162415
0.860278
0.139722
0.198405
0.24237
0.637196
1.85772
e-a(θ-b)
θs+1
2
0.343
1.3429985
Next
Estimate
^
Item
No
1
2
3
4
5
b
u
a
^
θs
q=1-p
a(u-p)
1.50
0.42
2.29
0.92
0.28
1
0
0
1
1.42
1.42
1.42
1.42
1.343
1.343
1.343
1.343
0.22294
-1.3107
1.34474
-0.6007
1.249746
0.269642
3.837189
0.54845
0.444495
0.787624
0.206732
0.645807
0.555505
0.212376
0.793268
0.354193
0.788818
-1.11843
-0.29356
0.502954
0.49789
0.33729
0.33068
0.46123
1
1.42
1.343
-2.3047
0.099793
0.909262
0.090738
0.128848
0.16636
0.008634
1.79345
-a(θb)
-a(θ-b)
e
p=1/(1+ea(θ-b)
)
Correction
a *p*q
Factor
θs+1
2
0.00481
106
1.3478144
Next
Estimate
^
Item
No
1
2
3
4
5
b
u
a
^
θs
q=1-p
a(u-p)
1.50
0.42
2.29
0.92
0.28
1
0
0
1
1.42
1.42
1.42
1.42
1.348
1.348
1.348
1.348
0.21584
-1.3178
1.33764
-0.6078
1.240904
0.267734
3.810041
0.544569
0.446249
0.788809
0.207898
0.64743
0.553751
0.211191
0.792102
0.35257
0.786327
-1.12011
-0.29522
0.50065
0.49827
0.33591
0.33205
0.46027
1
1.42
1.348
-2.3118
0.099087
0.909846
0.090154
0.128018
0.1654
-0.00033
1.79191
-a(θb)
p=1/(1+ea(θ-b)
)
-a(θ-b)
e
Correction
a *p*q
Factor
-0.00018
At this point, the procedure is terminated because the value of the adjustment 0.002 is very
small. Thus, the test taker’s estimated ability is 1.348. So, the best way to do that is estimate
it. However, this does not prevent us from conceptualizing such a parameter. Fortunately, one
can obtain a standard error of the estimated ability that provides some indication of the
precision of the estimate. The underlying principle is that a test taker, hypothetically, could
take the same test a large number of times, assuming that he does not remember
^
how he answered the previous test items. An ability estimate θ would be obtained from each
testing. The standard error is a measure of the variability of
^
the values of θ around the test taker’s unknown parameter value θ. For other scores of test
takers namely 4, 2 & 1(in separate worksheets) same procedure is adopted. In the present
case, an estimated standard error can be computed using the equation given below:
∧
S .E (θ ) =
1
N
∧
∧
∑ a P(θ )Q(θ )
2
θs+1
2
i =1
In the equation given above, the term under the square root sign is the denominator of the
estimation equation. As a result, the estimated standard error can be obtained as a side
product of estimating the test taker’s ability. In the illustrated example given above, it will be
calculated as shown below:
107
1.3478164
∧
S .E (θ ) =
1
= 0.746
1.793
Thus, the test taker’s ability is not estimated very precisely because the standard error 0.746
is very large. This is primarily due to the fact that only five items were used here and one
would not expect a very good estimate.
Looking into the PH3 output of BILOG, test taker #3 has an ability of 1.266 as against 1.347.
There are two cases for which the maximum likelihood estimation procedure fails to yield an
ability estimate. First, when a test taker answers none of the items correctly, the
corresponding ability estimate is negative infinity. Second, when a test taker answers all the
items in the test correctly, the corresponding ability estimate is positive infinity. In both of
these cases it is impossible to obtain an ability estimate for the test taker (the computer
literally cannot compute a number as big as infinity). Consequently, the computer programs
used to estimate ability must protect themselves against these two conditions. When they
detect either a test score of zero or a perfect test score, they will eliminate the test taker from
further analysis and set the estimated ability to some symbol such as ****** to indicate what
has happened.
Item Invariance of a Test Taker’s Ability Estimate
Another basic principle of IRT is that the test taker’s ability is invariant with respect to the
items used to determine it. This principle rests upon two conditions: first, all the items
measure the same underlying latent trait; second, the values of all the item parameters are in
a common metric.
To illustrate this principle, assume that a test taker has an ability score of zero, which places
him at the middle of the ability scale. Now, if a set of ten items having an average difficulty of
-2 were administered to this test taker, the item
^
responses could be used to estimate the examinee’s ability, yielding θ1 for this test. Then if a
second set of ten items having an average difficulty of +1 were administered to this test taker,
these item responses could be used to estimate
^
the test taker’s ability, yielding θ2 for this second test. Under the item invariance
^ ^
108
principle, θ1= θ2; that is the two sets of items should yield the same ability estimate, within
sampling variation, for the test taker. In addition, there is no requirement that the
discrimination parameters be the same for the two sets of items. This principle is just a
reflection of the fact that the ICC spans the whole ability scale. Just as any sub-range of the
ability scale can be used in the estimation of item parameters, the corresponding segments of
several ICCs can be used to estimate a test taker’s ability. Items with a high average difficulty
will have a point on their ICCs that corresponds to the ability of interest. Similarly, items with a
low average difficulty will have a point on their ICCs that corresponds to the ability of interest.
Consequently, either set of items can be used to estimate the ability of test takers at that
point. In each set, a different part of the ICC is involved, but that is acceptable. The practical
implication of this principle is that a test located anywhere along the ability scale can be used
to estimate a test taker’s ability.
For instance, a test taker could take a test that is “easy” or a test that is “hard” and obtain, on
the average, the same estimated ability. This is in sharp contrast to CTT, where such a test
taker would get a high test score on the easy test, a low score on the hard test, and there
would be no way of ascertaining the test taker’s underlying ability. Under IRT, the test taker’s
ability is fixed and invariant with respect to the items used to measure it. A word of caution
here with respect to the meaning of the word “fixed” is that a test taker’s ability is fixed only in
the sense that it has a particular value in a given context. For example, if a test taker took the
same test several times assuming he does not remember the items or the responses from test
to test then the test taker’s ability would be fixed. However, if the test taker received remedial
instruction between the tests or if there were carryover effects, the test taker’s underlying
ability level would be different for each testing. Thus, the test taker’s underlying ability level is
not immutable. There are a number of applications of IRT that depend upon a test taker’s
ability level changing as a function of changes in the educational context. The item invariance
of a test taker’s ability and the group invariance of an item’s parameters are two facets of the
invariance principle of IRT. This principle is the basis for a number of practical applications of
the theory.
A twenty-item test administered to 76 test takers yielded the following true scores for each
one of them. Let us look at a test taker having a score of 15. His true score works out to be
10.41. In terms of percentage, this is equal to 10.41/20 = 52.05%. When the same test taker
takes only the test with odd numbered items, the true score comes out to be 5.28. Similarly,
his true score on the even numbered items comes out to be 5.13. In terms of percentages,
they will be 5.28/10=52.8% and 5.13/10=51.3% respectively. The error in the estimate of the
percentage for the same test taker, if he takes only odd or even numbered items, works out to
52.8-52.05=0.75%. And for odd, the error is 52.05-51.3=0.75%. This is negligible and can be
accounted for a small sample. Thus, item invariance is proved from this example. Hence, a
test taker’s true score is not dependent on the items he takes.
109
Test
Taker
No
Tried
No
Right
Ability
1
20
18
1.4636
2
20
18
1.4636
3
20
18
1.4636
4
20
18
1.4636
5
20
17
1.1712
6
20
17
1.1712
7
20
17
1.1712
8
20
17
1.1712
9
20
16
0.8881
10
20
16
0.8881
11
20
16
0.8881
12
20
16
0.8881
13
20
16
0.8881
14
20
15
0.6133
15
20
15
0.6133
16
20
15
0.6133
17
20
15
0.6133
18
20
15
0.6133
19
20
15
0.6133
20
20
15
0.6133
21
20
15
0.6133
22
20
15
0.6133
23
20
15
0.6133
24
20
15
0.6133
25
20
15
0.6133
26
20
14
0.3456
True
Score
Odd TS
Even TS
11.77
5.82
5.95
11.77
5.82
5.95
11.77
5.82
5.95
11.77
5.82
5.95
11.31
5.58
5.72
11.31
5.58
5.72
11.31
5.58
5.72
11.31
5.58
5.72
10.85
5.35
5.50
10.85
5.35
5.50
10.85
5.35
5.50
10.85
5.35
5.50
10.85
5.35
5.50
10.41
5.13
5.28
10.41
5.13
5.28
10.41
5.13
5.28
10.41
5.13
5.28
10.41
5.13
5.28
10.41
5.13
5.28
10.41
5.13
5.28
10.41
5.13
5.28
10.41
5.13
5.28
10.41
5.13
5.28
10.41
5.13
5.28
10.41
5.13
5.28
110
27
20
14
0.3456
28
20
14
0.3456
29
20
14
0.3456
30
20
14
0.3456
31
20
14
0.3456
32
20
14
0.3456
33
20
13
0.0839
34
20
13
0.0839
35
20
13
0.0839
36
20
13
0.0839
37
20
13
0.0839
38
20
13
0.0839
39
20
13
0.0839
40
20
13
0.0839
41
20
13
0.0839
42
20
13
0.0839
43
20
13
0.0839
44
20
12
-0.1726
45
20
12
-0.1726
46
20
12
-0.1726
47
20
12
-0.1726
48
20
12
-0.1726
49
20
12
-0.1726
50
20
12
-0.1726
51
20
11
-0.4247
52
20
11
-0.4247
9.97
4.91
5.06
9.97
4.91
5.06
9.97
4.91
5.06
9.97
4.91
5.06
9.97
4.91
5.06
9.97
4.91
5.06
9.97
4.91
5.06
9.54
4.70
4.85
9.54
4.70
4.85
9.54
4.70
4.85
9.54
4.70
4.85
9.54
4.70
4.85
9.54
4.70
4.85
9.54
4.70
4.85
9.54
4.70
4.85
9.54
4.70
4.85
9.54
4.70
4.85
9.54
4.70
4.85
9.13
4.49
4.64
9.13
4.49
4.64
9.13
4.49
4.64
9.13
4.49
4.64
9.13
4.49
4.64
9.13
4.49
4.64
9.13
4.49
4.64
8.72
4.29
4.44
8.72
4.29
4.44
111
53
20
11
-0.4247
54
20
11
-0.4247
55
20
11
-0.4247
56
20
11
-0.4247
57
20
11
-0.4247
58
20
11
-0.4247
59
20
11
-0.4247
60
20
11
-0.4247
61
20
11
-0.4247
62
20
10
-0.6736
63
20
10
-0.6736
64
20
10
-0.6736
65
20
10
-0.6736
66
20
10
-0.6736
67
20
9
-0.9203
68
20
9
-0.9203
69
20
9
-0.9203
70
20
9
-0.9203
71
20
9
-0.9203
72
20
9
-0.9203
73
20
8
-1.1654
74
20
8
-1.1654
75
20
7
-1.4095
76
20
6
-1.6539
8.72
4.29
4.44
8.72
4.29
4.44
8.72
4.29
4.44
8.72
4.29
4.44
8.72
4.29
4.44
8.72
4.29
4.44
8.72
4.29
4.44
8.72
4.29
4.44
8.72
4.29
4.44
8.33
4.09
4.24
8.33
4.09
4.24
8.33
4.09
4.24
8.33
4.09
4.24
8.33
4.09
4.24
7.94
3.90
4.04
7.94
3.90
4.04
7.94
3.90
4.04
7.94
3.90
4.04
7.94
3.90
4.04
7.94
3.90
4.04
7.56
3.71
3.85
7.56
3.71
3.85
7.19
3.52
3.67
6.83
3.34
3.48
112
Test Calibration
While assuming the metric scale to be known, the numerical values of the item parameters
and the test taker’s ability parameters can be expressed in this metric. Test constructors while
writing an item, know what trait they want the item to measure and whether the item is
designed to function among low, medium or high ability test takers. But it is not possible to
determine the values of the item’s parameters a priori. In addition, when a test is administered
to a group of test takers, it is not known in advance how much of the latent trait each of the
test takers possesses. As a result, a major task is to determine the values of the item
parameters and test taker’s ability in a metric for the underlying latent trait. In IRT, this task is
called test calibration, and it provides a frame of reference for interpreting test results.
Test calibration is accomplished by administering a test to a group of M examinees and
dichotomously scoring the test taker’s responses to the N items. Then mathematical
procedures are applied to the item response data in order to create an ability scale that is
unique to the particular combination of test items and test takers. Then the values of the item
parameter estimates and the test taker’s estimated abilities are expressed in this metric. Once
this is accomplished, the test has been calibrated, and the test results can be interpreted
through the constructs of IRT.
Test Calibration Process
The procedure used to calibrate a test was proposed by Birnbaum in 1968 and has been
implemented in widely used computer programs such as BICAL (Wright and Mead, 1976) and
LOGIST (Wingersky, Barton and Lord, 1982). The Birnbaum paradigm is an iterative procedure
employing two stages of maximum likelihood estimation. In one stage, the parameters of the
N items in the test are estimated, and in the second stage, the ability parameters of the M test
takers are estimated. The two stages are performed iteratively until stable sets of parameter
estimates are obtained. At this point, the test has been calibrated and an ability scale metric
defined.
Within the first stage of the Birnbaum paradigm, the estimated ability of each test taker is
treated as if it is expressed in the true metric of the latent trait. Then the parameters of each
item in the test are estimated via the maximum likelihood procedure. This is done one item at
a time, because an underlying assumption is that the items are independent of each other.
The result is a set of values for the estimates of the parameters of the items in the test.
The second stage assumes that the item parameter estimates yielded by the first stage are
actually the values of the item parameters. Then, the ability of each test taker is estimated
using the maximum likelihood procedure. It is assumed that the ability of each test taker is
independent of all other test takers. Hence, the ability estimates are obtained one test taker at
113
a time. The two-stage process is repeated until some suitable convergence criterion is met.
The overall effect is that the parameters of the N test items and the ability levels of the M test
takers have been estimated simultaneously, even though they were done one at a time. This
clever paradigm reduces a very complex estimation problem to one that can be implemented
on a computer.
The Metric Problem
An unfortunate feature of the Birnbaum paradigm is that it does not yield a unique metric for
the ability scale. This means that the midpoint and the unit of measurement of the obtained
ability scale are indeterminate implying that many different values work equally well. In
technical terms, the metric is unique up to a linear transformation. As a result, it is necessary
to “anchor” the metric via arbitrary rules for determining the midpoint and unit of
measurement of the ability scale. How this is done is up to the persons implementing the
Birnbaum paradigm in a computer program. In the BICAL computer program, this anchoring
process is performed after the first stage is completed. Thus, each of two stages within
iteration is performed using a slightly different ability scale metric. As the overall iterative
process converges, the metric of the ability scale also converges to a particular midpoint and
unit of measurement. The crucial feature of this process is that the resulting ability scale
metric depends upon the specific set of items constituting the test and the responses of a
particular group of test takers to that test. It is not possible to obtain estimates of the test
taker’s ability and of the item parameters in the true metric of the underlying latent trait. The
best we can do is obtaining a metric that depends upon a particular combination of test takers
and test items.
Summary of the Test Calibration Process
To obtain calibrated items, one has to:
•
•
•
Write them,
Estimate their parameters, and
Make sure that the estimates are on the same scale.
The end product of the test calibration process is the definition of an ability scale metric.
Under the Rasch model, this scale has a unit of measurement of 1 and a midpoint of zero.
Superficially this looks exactly the same as the ability scale metric used in previous chapters.
However, it is not the metric of the underlying latent trait. The obtained metric depends upon
the item responses yielded by a particular combination of test takers and test items being
subjected to the Birnbaum paradigm. Since the true metric of the underlying latent trait
114
cannot be determined, the metric yielded by the Birnbaum paradigm is used as if it were the
true metric. The obtained item difficulty values and the test taker’s ability are interpreted in
this metric. Thus, the test has been calibrated. The outcome of the test calibration procedure
is to locate each test taker and item along the obtained ability scale.
In the present example, item 5 had a difficulty of -1 and test taker 10 had an ability estimate
of -0.91. Therefore, the probability of test taker 10 answering item 5 correctly is approximately
0.5. The capability to locate items and test takers along a common scale is a powerful feature
of item response theory. This feature allows one to interpret the results of a test calibration
within a single framework and provides meaning to the values of the parameter estimates.
The Likelihood Function
A test taker taking a test under Single Parameter model, with k items can obtain one of k + 1
observed scores (0, 1, , , , , k). However, the number of the possible responses to the test
(the response patterns) is much larger: 2k. For a test of 5 items, there are 32 distinct response
patterns. Each of them has a certain probability. Because every test taker must have some
response pattern and the response patterns are mutually exclusive, their probabilities will sum
to 1. This is true for the data set as a whole, and it is also true at any specific level of ability.
Let us look at how to calculate the probability that a test taker of ability θj will respond to the
test with a certain pattern, e.g. (True, True, False, True, False). We already know how to
calculate the probability of each response in the pattern separately: P (θj, b1), P (θj, b2). . .
Q (θj, b5), but what is their joint probability? IRT makes the important assumption of local
independence. This means that the responses given to the separate items in a test are
mutually independent, when ability is given. The actually observed responses may be
correlated, even strongly correlated — but this is only because the responses of test takers
with widely different abilities have been put together, ignoring ability. If we consider only test
takers having the same latent ability, the correlations between the responses are supposed to
vanish.
Now, because P (θj, b1), P(θj, b2), . . . , Q(θj, b5) are functions of θj, we can multiply them to
obtain the probability of the whole pattern. This follows from the assumption of conditional
independence, according to which the responses given to the individual items in a test are
mutually independent given θ. The function is as shown below:
L(θ ) = ∏ Pi (θ , bi ) Qi (θ , bi )1−ui
ui
i
115
Where ui ε (0, 1) is the score on item i, is called the likelihood function. It is the probability of
a response pattern given the ability θ and of course, the item parameters. There is one
likelihood function for each response pattern, and the sum of all such functions equals 1 at
any value of θ.
The likelihood is in fact a probability. The subtle difference between the two concepts has
more to do with how we use them than with what they really are. Probabilities usually point
from a theoretically assumed quantity to the data that may be expected to emerge: thus, the
IRT model predicts the probability of any response to a test given the true ability of the test
taker. The likelihood works in the opposite direction: it is used by the same IRT model to
predict latent ability from the observed responses.
The Maximum Likelihood Estimate of Ability
Let us look at a more conventional approach to ability estimation, which is based on the
^
principle of maximum likelihood. The ability, say θ, which has the highest likelihood given the
observed pattern (and the item parameters), will become the ability estimate.
Figure: Finding the ability estimates by maximum likelihood
In the figure above, the likelihood inunctions shown in blue for the response patterns
(T,F,F,F,F), (T,T,F,F,F), (T,T,T,F,F), and (T,T,T,T,F). It is easy to see that the likelihood
functions peak exactly at the ability estimates found earlier. Hence, maximum likelihood will
produce the same estimates of ability as the previous method. In the Single Parameter model,
116
the ability estimate depends only on how many items were answered correctly, not on which
items got the correct responses. This does not mean that the likelihood functions are invariant
to the response pattern; it only means that the likelihood functions for patterns having the
same number of correct responses peak at the same ability level.
Figure : Likelihood functions for various response patterns having the same total score of 1
The above figure shows the likelihood functions for the five response patterns having the
same total score of 1. All five functions lead to the same ability estimate even if they are not
the same functions. It is easy to see why the likelihood functions are different: when a test
taker can only get one item right, we expect this to be the easiest item, and we would be
somewhat surprised if it turns out to be the most difficult item instead. The accompanying
applet lets you manipulate the item difficulties and choose different response patterns
simultaneously. To finish with the Single Parameter model, there is yet another applet that
brings together most of what we have learnt so far: the item response functions, the test
response function, the likelihood function, and two alternative ways to estimate ability, the
test information function, and the standard error of measurement.
Test and Item Analysis through IRT using Application
Software
117
It was mentioned that IRT enables fairly accurate test and item analysis. Traditional test
analyses will yield all CTT characteristics like Mean/Median/Mode, S.D, Variance, S.E of Mean,
Range of Scores, Quartiles, Skewness and Kurtosis. These are exactly the descriptive statistics.
The first output from application software through IRT yields all the above and a proportion of
the correct responses to every item, item test, score correlation, point biserial to give
discrimination. But, important outputs follow namely that of item characteristic estimates of
parameters. Depending upon either a One, Two or Three Parameter models, the output will
give threshold (b=item difficulty), slope (a=discrimination) and asymptote (c=guessing
parameter). This can be to any decimal of accuracy needed but in the maximum likelihood
estimates using successive approximation the last two trials will be made not to differ more
than 0.001 or 0.002 etc. S.E of each of these estimates is also a part of the output; so is the
Chi-square confirming this goodness of fit of the exponential curve to the data. It must be
noted that the numerical values of these estimates are on a metric from -3 to +3 or -4 to +4
and actual values may be different for these items of different models. Thus, the values for
item characteristics and test taker ability are specific to the model chosen. These are the
location and shape parameters. While calibrating the test items, it is essential to specify a
model namely Rasch, Birnbaum or Fred Lord. Based on this specification items (item
characteristics) can be further used for these characteristics.
There are several software available in the market for securing a license to use. They are
namely, BICAL (Benjamin Wright), BILOG (Scientific Software International) and MULTILOG
etc. In addition, Frank Baker has provided a software along with an eBook which enables the
understanding of various concepts and principles (otherwise very difficult to prove
mathematically) underlying IRT. This is very valuable software available free on the Net. This
eBook also has BIRT software (Basics of IRT by Baker). The readers are encouraged to use
this software to understand, verify and clarify such difficult concepts through practical
exercises. The BICAL software has been illustrated through an example given earlier as
Benjamin Wright’s Mathematical Formulation. The detailed procedure for using the BIRT
software is given in the Appendix.
Examples
Following are two examples of tests run through BILOG:
1. Test of 5 items administered on 10 test takers
•
A complete report illustrating both CTT and IRT and their outputs can be seen by
clicking here.
2. Test of 20 items administered on 76 test takers
A complete set of outputs adopting all three models illustrating IRT can be seen by
clicking on
118
Outputs for a Single Parameter model are:
1
BILOG-MG V3.0
REV 19990104.1300
BILOG-MG ITEM MAINTENANCE PROGRAM: LOGISTIC ITEM RESPONSE
MODEL
DISTRIBUTED BY
SCIENTIFIC SOFTWARE INTERNATIONAL, INC.
7383 N. LINCOLN AVENUE, SUITE 100
CHICAGO, IL 60646
(800) 247-6113
(847) 675-0720
WWW: http:://www.ssicentral.com
PROGRAM COPYRIGHT HELD BY SCIENTIFIC SOFTWARE
INTERNATIONAL, INC. 2002
DISTRIBUTION OR USE UNAUTHORIZED BY SSI, INC. IS PROHIBITED
1
*** BILOG-MG ITEM MAINTENANCE PROGRAM ***
*** PHASE 1 ***
sample 20 by 76
>GLOBAL DFName = 'C:\drvn\ss.dat',
NPArm = 1,
LOGistic,
119
SAVe;
FILE ASSIGNMENT AND DISPOSITION
===============================
SUBJECT DATA INPUT FILE C:\DRVN\SS.DAT
BILOG-MG MASTER DATA FILE MF.DAT
WILL BE CREATED FROM DATA FILE
CALIBRATION DATA FILE
CF.DAT
ITEM PARAMETERS FILE
IF.DAT
WILL BE CREATED THIS RUN
CASE SCALE-SCORE FILE
CASE WEIGHTING
SF.DAT
NONE EMPLOYED
ITEM RESPONSE MODEL
1 PARAMETER LOGISTIC
LOGIT METRIC (I.E., D = 1.0)
>SAVE MASter = 'ruchi.MAS',
CALib = 'ruchi.CAL',
PARm = 'ruchi.PAR',
SCOre = 'ruchi.SCO',
COVariance = 'ruchi.COV',
TSTat = 'ruchi.TST',
120
ISTat = 'ruchi.IST';
BILOG-MG SAVE FILES
[OUTPUT FILES]
BILOG-MG MASTER BINARY DATA RUCHI.MAS
CALIBRATION BINARY DATA FILERUCHI.CAL
CLASSICAL ITEM STATISTICS RUCHI.IST
RUCHI.PAR
RUCHI.SCO
ESTIMATED COVARIANCE FILE RUCHI.COV
TEST INFORMATION FILE
RUCHI.TST
>LENGTH NITems = (20);
TEST LENGTH SPECIFICATIONS
==========================
MAIN TEST LENGTHS:
20
>INPUT NTOtal = 20,
NALt = 3,
121
NIDchar = 10;
DATA INPUT SPECIFICATIONS
=========================
NUMBER OF FORMAT LINES
1
NUMBER OF ITEMS IN INPUT STREAM
20
NUMBER OF RESPONSE ALTERNATIVES
3
NUMBER OF SUBJECT ID CHARACTERS
10
NUMBER OF GROUPS
1
NUMBER OF TEST FORMS
1
TYPE OF DATA
SINGLE-SUBJECT DATA, NO CASE WEIGHTS
MAXIMUM SAMPLE SIZE FOR ITEM CALIBRATION 10000000
ALL SUBJECTS INCLUDED IN RUN
>ITEMS ;
TEST SPECIFICATIONS
===================
>TEST1 TNAme = 'TEST0001',
INUmber = (1(1)20);
TEST NUMBER: 1 TEST NAME: TEST0001
NUMBER OF ITEMS: 20
ITEM ITEM
ITEM ITEM
ITEM ITEM
ITEM ITEM
122
NUMBER NAME NUMBER NAME
NUMBER NAME
NUMBER
NAME
----------------------------------------------------------------------1 ITEM0001
7 ITEM0007
13 ITEM0013 19 ITEM0019
2 ITEM0002
8 ITEM0008
14 ITEM0014 20 ITEM0020
3 ITEM0003
9 ITEM0009 15 ITEM0015
4 ITEM0004 10 ITEM0010 16 ITEM0016
5 ITEM0005 11 ITEM0011 17 ITEM0017
6 ITEM0006 12 ITEM0012 18 ITEM0018
-----------------------------------------------------------------------
FORM SPECIFICATIONS
===================
ITEMS READ ACCORDING TO SPECIFICATIONS ON THE ITEMS COMMAND
FORMAT FOR DATA INPUT IS:
(10A1, 20A1)
OBSERVATION #
1 WEIGHT:
1.0000 ID : Examinee01
SUBTEST #: 1 TEST0001
GROUP #: 1
TRIED RIGHT
20.000 18.000
123
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0
OBSERVATION #
2 WEIGHT:
GROUP #: 1
TRIED RIGHT
20.000 18.000
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 1.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0
76 OBSERVATIONS READ FROM FILE: C:\DRVN\SS.DAT
76 OBSERVATIONS WRITTEN TO FILE: RUCHI.MAS
ITEM STATISTICS FOR SUBTEST TEST0001
ITEM*TEST CORRELATION
124
ITEM NAME
#TRIED #RIGHT PCT
LOGIT PEARSON BISERIAL
------------------------------------------------------------------------1 ITEM0001 76.0 43.0 56.6 -0.26 0.366 0.462
2 ITEM0002 76.0 66.0 86.8 -1.89 0.116 0.184
3 ITEM0003 76.0 56.0 73.7 -1.03 0.212 0.286
4 ITEM0004 76.0 60.0 78.9 -1.32 0.089 0.125
5 ITEM0005 76.0 28.0 36.8 0.54 0.213 0.272
6 ITEM0006 76.0 61.0 80.3 -1.40 0.238 0.341
7 ITEM0007 76.0 64.0 84.2 -1.67 0.222 0.335
8 ITEM0008 76.0 47.0 61.8 -0.48 0.320 0.408
9 ITEM0009 76.0 41.0 53.9 -0.16 -0.019 -0.024
10 ITEM0010 76.0 35.0 46.1 0.16 0.430 0.539
11 ITEM0011 76.0 34.0 44.7 0.21 0.341 0.429
12 ITEM0012 76.0 46.0 60.5 -0.43 0.303 0.385
13 ITEM0013 76.0 63.0 82.9 -1.58 0.099 0.146
14 ITEM0014 76.0 39.0 51.3 -0.05 0.074 0.093
15 ITEM0015 76.0 57.0 75.0 -1.10 0.141 0.192
16 ITEM0016 76.0 54.0 71.1 -0.90 0.019 0.025
17 ITEM0017 76.0 70.0 92.1 -2.46 0.049 0.089
18 ITEM0018 76.0 59.0 77.6 -1.24 0.009 0.013
19 ITEM0019 76.0 52.0 68.4 -0.77 0.039 0.051
20 ITEM0020 76.0
4.0 5.3 2.89 0.187 0.388
-------------------------------------------------------------------------
296 BYTES OF NUMERICAL WORKSPACE USED OF 8192000 AVAILABLE
IN PHASE-1
2216 BYTES OF CHARACTER WORKSPACE USED OF 2048000 AVAILABLE
IN PHASE-1
11/01/2011 15:59:46
PH1
PH2
1
125
BILOG-MG V3.0
REV 19990329.1300
MODEL
*** PHASE 2 ***
sample 20 by 76
>CALIB ACCel = 1.0000;
CALIBRATION PARAMETERS
======================
MAXIMUM NUMBER OF EM CYCLES:
20
MAXIMUM NUMBER OF NEWTON CYCLES:
CONVERGENCE CRITERION:
0.0100
ACCELERATION CONSTANT:
1.0000
2
LATENT DISTRIBUTION:
NORMAL PRIOR FOR EACH GROUP
PLOT EMPIRICAL VS. FITTED ICC'S:
NO
DATA HANDLING:
DATA ON SCRATCH FILE
CONSTRAINT DISTRIBUTION ON SLOPES:
NO
CONSTRAINT DISTRIBUTION ON THRESHOLDS: NO
1
--------------------------------------------------------------------------------
******************************
126
CALIBRATION OF MAINTEST
TEST0001
******************************
METHOD OF SOLUTION:
EM CYCLES (MAXIMUM OF 20)
FOLLOWED BY NEWTON-RAPHSON STEPS (MAXIMUM OF 2)
QUADRATURE POINTS AND PRIOR WEIGHTS:
1
2
3
4
5
POINT -0.4000E+01 -0.3429E+01 -0.2857E+01 -0.2286E+01 -0.1714E+01
WEIGHT 0.7648E-04 0.6387E-03 0.3848E-02 0.1673E-01 0.5245E-01
6
7
8
9
10
POINT -0.1143E+01 -0.5714E+00 -0.8882E-15 0.5714E+00 0.1143E+01
WEIGHT 0.1186E+00 0.1936E+00 0.2280E+00 0.1936E+00 0.1186E+00
11
12
13
14
15
POINT 0.1714E+01 0.2286E+01 0.2857E+01 0.3429E+01 0.4000E+01
WEIGHT 0.5245E-01 0.1673E-01 0.3848E-02 0.6387E-03 0.7648E-04
[E-M CYCLES]
127
-2 LOG LIKELIHOOD =
CYCLE
1; LARGEST CHANGE= 0.11064
-2 LOG LIKELIHOOD =
CYCLE
1660.494
-2 LOG LIKELIHOOD =
CYCLE
1660.713
-2 LOG LIKELIHOOD =
CYCLE
1661.284
-2 LOG LIKELIHOOD =
CYCLE
1663.262
-2 LOG LIKELIHOOD =
CYCLE
1669.105
1660.485
[NEWTON CYCLES]
-2 LOG LIKELIHOOD:
1660.4845
128
CYCLE
INTERVAL COUNTS FOR COMPUTATION OF ITEM CHI-SQUARES
---------------------------------------------------------------------------0. 2. 8. 16. 18. 7. 17. 4. 4.
---------------------------------------------------------------------------INTERVAL AVERAGE THETAS
---------------------------------------------------------------------------******* -2.123 -1.433 -0.805 -0.141 0.366 0.861 1.538 1.947
---------------------------------------------------------------------------1
SUBTEST TEST0001; ITEM PARAMETERS AFTER CYCLE 7
ITEM
CHISQ
INTERCEPT SLOPE THRESHOLD LOADING ASYMPTOTE
DF
S.E.
S.E.
S.E.
S.E.
S.E. (PROB)
------------------------------------------------------------------------------ITEM0001 | 0.287 | 0.577 | -0.497 | 0.500 | 0.000 | 3.2 5.0
| 0.253* | 0.087* | 0.439* | 0.075* | 0.000* | (0.6644)
|
|
|
|
|
|
ITEM0002 | 2.008 | 0.577 | -3.479 | 0.500 | 0.000 | 1.0 2.0
| 0.347* | 0.087* | 0.601* | 0.075* | 0.000* | (0.5997)
|
|
|
|
|
|
ITEM0003 | 1.107 | 0.577 | -1.917 | 0.500 | 0.000 | 0.5 4.0
| 0.274* | 0.087* | 0.475* | 0.075* | 0.000* | (0.9779)
|
|
|
|
|
|
ITEM0004 | 1.416 | 0.577 | -2.453 | 0.500 | 0.000 | 3.0 4.0
| 0.289* | 0.087* | 0.501* | 0.075* | 0.000* | (0.5635)
|
|
|
|
|
|
ITEM0005 | -0.581 | 0.577 | 1.006 | 0.500 | 0.000 | 3.4 3.0
| 0.253* | 0.087* | 0.438* | 0.075* | 0.000* | (0.3403)
|
|
|
|
|
|
ITEM0006 | 1.501 | 0.577 | -2.601 | 0.500 | 0.000 | 1.1 3.0
| 0.303* | 0.087* | 0.525* | 0.075* | 0.000* | (0.7653)
|
|
|
|
|
|
ITEM0007 | 1.786 | 0.577 | -3.094 | 0.500 | 0.000 | 1.0 4.0
129
| 0.329* | 0.087* | 0.571* | 0.075* | 0.000* | (0.9088)
|
|
|
|
|
|
ITEM0008 | 0.522 | 0.577 | -0.904 | 0.500 | 0.000 | 8.8
| 0.256* | 0.087* | 0.443* | 0.075* | 0.000* | (0.1178)
|
|
|
|
|
|
ITEM0009 | 0.172 | 0.577 | -0.297 | 0.500 | 0.000 | 4.8
| 0.233* | 0.087* | 0.403* | 0.075* | 0.000* | (0.3136)
|
|
|
|
|
|
ITEM0010 | -0.170 | 0.577 | 0.295 | 0.500 | 0.000 | 6.2
| 0.256* | 0.087* | 0.443* | 0.075* | 0.000* | (0.1863)
|
|
|
|
|
|
ITEM0011 | -0.227 | 0.577 | 0.394 | 0.500 | 0.000 | 4.0
| 0.251* | 0.087* | 0.436* | 0.075* | 0.000* | (0.4074)
|
|
|
|
|
|
ITEM0012 | 0.462 | 0.577 | -0.800 | 0.500 | 0.000 | 4.8
| 0.254* | 0.087* | 0.439* | 0.075* | 0.000* | (0.3057)
|
|
|
|
|
|
ITEM0013 | 1.686 | 0.577 | -2.920 | 0.500 | 0.000 | 2.6
| 0.311* | 0.087* | 0.539* | 0.075* | 0.000* | (0.4497)
|
|
|
|
|
|
ITEM0014 | 0.058 | 0.577 | -0.100 | 0.500 | 0.000 | 3.1
| 0.237* | 0.087* | 0.411* | 0.075* | 0.000* | (0.7944)
|
|
|
|
|
|
ITEM0015 | 1.180 | 0.577 | -2.044 | 0.500 | 0.000 | 5.6
| 0.274* | 0.087* | 0.476* | 0.075* | 0.000* | (0.2303)
|
|
|
|
|
|
ITEM0016 | 0.966 | 0.577 | -1.674 | 0.500 | 0.000 | 3.6
| 0.257* | 0.087* | 0.446* | 0.075* | 0.000* | (0.4635)
|
|
|
|
|
|
ITEM0017 | 2.596 | 0.577 | -4.498 | 0.500 | 0.000 | 0.1
| 0.432* | 0.087* | 0.749* | 0.075* | 0.000* | (0.9358)
|
|
|
|
|
|
ITEM0018 | 1.334 | 0.577 | -2.312 | 0.500 | 0.000 | 5.1
| 0.280* | 0.087* | 0.485* | 0.075* | 0.000* | (0.2797)
|
|
|
|
|
|
ITEM0019 | 0.833 | 0.577 | -1.443 | 0.500 | 0.000 | 2.7
| 0.252* | 0.087* | 0.437* | 0.075* | 0.000* | (0.6171)
|
|
|
|
|
|
ITEM0020 | -3.042 | 0.577 | 5.271 | 0.500 | 0.000 | 0.4
| 0.526* | 0.087* | 0.911* | 0.075* | 0.000* | (0.0000)
5.0
4.0
4.0
4.0
4.0
3.0
6.0
4.0
4.0
2.0
4.0
4.0
0.0
130
------------------------------------------------------------------------------* STANDARD ERROR
LARGEST CHANGE = 0.002976
65.0 73.0
(0.7375)
-------------------------------------------------------------------------------
PARAMETER
MEAN STN DEV
----------------------------------THRESHOLD -1.203 2.092
QUADRATURE POINTS, POSTERIOR WEIGHTS, MEAN AND S.D.:
1
2
3
4
5
POINT
-0.4056E+01 -0.3477E+01 -0.2897E+01 -0.2318E+01 -0.1739E+01
POSTERIOR 0.1800E-04 0.2912E-03 0.2699E-02 0.1509E-01 0.5355E-01
6
7
8
9
10
POINT
-0.1159E+01 -0.5798E+00 -0.3433E-03 0.5791E+00 0.1158E+01
POSTERIOR 0.1247E+00 0.1973E+00 0.2232E+00 0.1879E+00 0.1181E+00
11
12
13
14
15
POINT
0.1738E+01 0.2317E+01 0.2897E+01 0.3476E+01 0.4056E+01
POSTERIOR 0.5447E-01 0.1790E-01 0.4051E-02 0.6145E-03 0.6174E-04
MEAN
S.D.
0.00000
1.00000
IN PHASE-2
IN PHASE-2
131
11/01/2011 15:59:47
PH3
1
BILOG-MG V3.0
MODEL
*** LOGISTIC MODEL ITEM ANALYSER ***
*** PHASE 3 ***
sample 20 by 76
>SCORE ;
PARAMETERS FOR SCORING, RESCALING, AND TEST AND ITEM
INFORMATION
METHOD OF SCORING SUBJECTS:
EXPECTATION A POSTERIORI
(EAP; BAYES ESTIMATION)
TYPE OF PRIOR:
NORMAL
SCORES WRITTEN TO FILE
RUCHI.SCO
TYPE OF RESCALING:
ruchi.PH3
NONE REQUESTED
132
ITEM AND TEST INFORMATION:
DOMAIN SCORE ESTIMATION:
NONE REQUESTED
NONE REQUESTED
QUAD
TEST NAME POINTS
----------------------1 TEST0001 10
----------------------1
******************************
SCORING
******************************
PRIOR DISTRIBUTION(S)
=====================
EAP SUBJECT ESTIMATION, TEST: TEST0001
QUADRATURE POINTS AND PRIOR WEIGHTS, MEAN AND S.D.:
1
2
3
4
5
POINT -0.4000E+01 -0.3111E+01 -0.2222E+01 -0.1333E+01 -0.4444E+00
WEIGHT 0.1190E-03 0.2805E-02 0.3002E-01 0.1458E+00 0.3213E+00
6
7
8
9
10
POINT 0.4444E+00 0.1333E+01 0.2222E+01 0.3111E+01 0.4000E+01
133
WEIGHT 0.3213E+00 0.1458E+00 0.3002E-01 0.2805E-02 0.1190E-03
MEAN
S.D.
1
0.0000
1.0000
GROUP SUBJECT IDENTIFICATION
MARGINAL
WEIGHT TEST TRIED RIGHT PERCENT ABILITY S.E. PROB
-------------------------------------------------------------------------1 Examinee01
|
|
1.00 TEST0001 20 18 90.00 | 1.4211 0.7288 | 0.001212
1 Examinee02
|
|
1.00 TEST0001 20 18 90.00 | 1.4211 0.7288 | 0.000467
1 Examinee03
|
|
1.00 TEST0001 20 18 90.00 | 1.4211 0.7288 | 0.000836
1 Examinee04
|
|
1.00 TEST0001 20 18 90.00 | 1.4211 0.7288 | 0.001620
1 Examinee05
|
|
1.00 TEST0001 20 17 85.00 | 1.1201 0.7156 | 0.000013
1 Examinee06
|
|
1.00 TEST0001 20 17 85.00 | 1.1201 0.7156 | 0.000689
1 Examinee07
|
|
1.00 TEST0001 20 17 85.00 | 1.1201 0.7156 | 0.000001
1 Examinee08
|
|
1.00 TEST0001 20 17 85.00 | 1.1201 0.7156 | 0.000296
1 Examinee09
|
|
1.00 TEST0001 20 16 80.00 | 0.8295 0.7035 | 0.000229
1 Examinee10
|
|
1.00 TEST0001 20 16 80.00 | 0.8295 0.7035 | 0.000000
1 Examinee11
|
|
1.00 TEST0001 20 16 80.00 | 0.8295 0.7035 | 0.000311
1 Examinee12
|
|
1.00 TEST0001 20 16 80.00 | 0.8295 0.7035 | 0.000887
1 Examinee13
|
|
1.00 TEST0001 20 16 80.00 | 0.8295 0.7035 | 0.000386
1 Examinee14
|
|
1.00 TEST0001 20 15 75.00 | 0.5484 0.6926 | 0.000034
1 Examinee15
|
|
1.00 TEST0001 20 15 75.00 | 0.5484 0.6926 | 0.000021
1 Examinee16
|
|
134
1.00 TEST0001
1 Examinee17
1.00 TEST0001
1 Examinee18
1.00 TEST0001
1 Examinee19
1.00 TEST0001
1 Examinee20
1.00 TEST0001
1 Examinee21
1.00 TEST0001
1 Examinee22
1.00 TEST0001
1 Examinee23
1.00 TEST0001
1 Examinee24
1.00 TEST0001
1 Examinee25
1.00 TEST0001
1 Examinee26
1.00 TEST0001
1 Examinee27
1.00 TEST0001
1 Examinee28
1.00 TEST0001
1 Examinee29
1.00 TEST0001
1 Examinee30
1.00 TEST0001
1 Examinee31
1.00 TEST0001
1 Examinee32
1.00 TEST0001
1 Examinee33
1.00 TEST0001
1 Examinee34
1.00 TEST0001
1 Examinee35
1.00 TEST0001
1 Examinee36
20
15
20
15
20
15
20
15
20
15
20
15
20
15
20
15
20
15
20
15
20
14
20
14
20
14
20
14
20
14
20
14
20
14
20
13
20
13
20
13
75.00 |
|
75.00 |
|
75.00 |
|
75.00 |
|
75.00 |
|
75.00 |
|
75.00 |
|
75.00 |
|
75.00 |
|
75.00 |
|
70.00 |
|
70.00 |
|
70.00 |
|
70.00 |
|
70.00 |
|
70.00 |
|
70.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
0.5484
|
0.5484
|
0.5484
|
0.5484
|
0.5484
|
0.5484
|
0.5484
|
0.5484
|
0.5484
|
0.5484
|
0.2753
|
0.2753
|
0.2753
|
0.2753
|
0.2753
|
0.2753
|
0.2753
|
0.0088
|
0.0088
|
0.0088
|
0.6926 | 0.000313
0.6926 | 0.000082
0.6926 | 0.000033
0.6926 | 0.000032
0.6926 | 0.000091
0.6926 | 0.000061
0.6926 | 0.000174
0.6926 | 0.000889
0.6926 | 0.000088
0.6926 | 0.000050
0.6835 | 0.000078
0.6835 | 0.000021
0.6835 | 0.000013
0.6835 | 0.000166
0.6835 | 0.000000
0.6835 | 0.000207
0.6835 | 0.000040
0.6756 | 0.000048
0.6756 | 0.000057
0.6756 | 0.000008
135
1.00 TEST0001
1 Examinee37
1.00 TEST0001
1 Examinee38
1.00 TEST0001
1 Examinee39
1.00 TEST0001
1 Examinee40
1.00 TEST0001
1 Examinee41
1.00 TEST0001
1 Examinee42
1.00 TEST0001
1 Examinee43
1.00 TEST0001
1 Examinee44
1.00 TEST0001
1 Examinee45
1.00 TEST0001
1 Examinee46
1.00 TEST0001
1 Examinee47
1.00 TEST0001
1 Examinee48
1.00 TEST0001
1 Examinee49
1.00 TEST0001
1 Examinee50
1.00 TEST0001
1 Examinee51
1.00 TEST0001
1 Examinee52
1.00 TEST0001
1 Examinee53
1.00 TEST0001
1 Examinee54
1.00 TEST0001
1 Examinee55
1.00 TEST0001
1 Examinee56
20
13
20
13
20
13
20
13
20
13
20
13
20
13
20
13
20
12
20
12
20
12
20
12
20
12
20
12
20
12
20
11
20
11
20
11
20
11
20
11
65.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
60.00 |
|
60.00 |
|
60.00 |
|
60.00 |
|
60.00 |
|
60.00 |
|
60.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
0.0088
|
0.0088
|
0.0088
|
0.0088
|
0.0088
|
0.0088
|
0.0088
|
0.0088
|
-0.2518
|
-0.2518
|
-0.2518
|
-0.2518
|
-0.2518
|
-0.2518
|
-0.2518
|
-0.5074
|
-0.5074
|
-0.5074
|
-0.5074
|
-0.5074
|
0.6756 | 0.000003
0.6756 | 0.000006
0.6756 | 0.000015
0.6756 | 0.000050
0.6756 | 0.000004
0.6756 | 0.000035
0.6756 | 0.000002
0.6756 | 0.000019
0.6684 | 0.000001
0.6684 | 0.000022
0.6684 | 0.000004
0.6684 | 0.000027
0.6684 | 0.000014
0.6684 | 0.000008
0.6684 | 0.000006
0.6630 | 0.000012
0.6630 | 0.000006
0.6630 | 0.000204
0.6630 | 0.000005
0.6630 | 0.000001
136
1.00 TEST0001
1 Examinee57
1.00 TEST0001
1 Examinee58
1.00 TEST0001
1 Examinee59
1.00 TEST0001
1 Examinee60
1.00 TEST0001
1 Examinee61
1.00 TEST0001
1 Examinee62
1.00 TEST0001
1 Examinee63
1.00 TEST0001
1 Examinee64
1.00 TEST0001
1 Examinee65
1.00 TEST0001
1 Examinee66
1.00 TEST0001
1 Examinee67
1.00 TEST0001
1 Examinee68
1.00 TEST0001
1 Examinee69
1.00 TEST0001
1 Examinee70
1.00 TEST0001
1 Examinee71
1.00 TEST0001
1 Examinee72
1.00 TEST0001
1 Examinee73
1.00 TEST0001
1 Examinee74
1.00 TEST0001
1 Examinee75
1.00 TEST0001
1 Examinee76
20
11
20
11
20
11
20
11
20
11
20
11
20
10
20
10
20
10
20
10
20
10
20
9
20
9
20
9
20
9
20
9
20
9
20
8
20
8
20
7
55.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
50.00 |
|
50.00 |
|
50.00 |
|
50.00 |
|
50.00 |
|
45.00 |
|
45.00 |
|
45.00 |
|
45.00 |
|
45.00 |
|
45.00 |
|
40.00 |
|
40.00 |
|
35.00 |
|
-0.5074
|
-0.5074
|
-0.5074
|
-0.5074
|
-0.5074
|
-0.5074
|
-0.7596
|
-0.7596
|
-0.7596
|
-0.7596
|
-0.7596
|
-1.0093
|
-1.0093
|
-1.0093
|
-1.0093
|
-1.0093
|
-1.0093
|
-1.2569
|
-1.2569
|
-1.5033
|
0.6630 | 0.000023
0.6630 | 0.000003
0.6630 | 0.000007
0.6630 | 0.000082
0.6630 | 0.000001
0.6630 | 0.000004
0.6593 | 0.000011
0.6593 | 0.000008
0.6593 | 0.000001
0.6593 | 0.000000
0.6593 | 0.000017
0.6562 | 0.000081
0.6562 | 0.000002
0.6562 | 0.000081
0.6562 | 0.000081
0.6562 | 0.000012
0.6562 | 0.000000
0.6538 | 0.000000
0.6538 | 0.000002
0.6534 | 0.000000
137
1.00 TEST0001 20 6 30.00 | -1.7501 0.6545 | 0.000001
--------------------------------------------------------------------------
SUMMARY STATISTICS FOR SCORE ESTIMATES
======================================
CORRELATIONS AMONG TEST SCORES
TEST0001
TEST0001
1.0000
MEANS, STANDARD DEVIATIONS, AND VARIANCES OF SCORE ESTIMATES
TEST:
TEST0001
MEAN:
-0.0006
S.D.:
0.7384
VARIANCE:
0.5452
ROOT-MEAN-SQUARE POSTERIOR STANDARD DEVIATIONS
TEST:
TEST0001
RMS:
0.6798
VARIANCE:
0.4622
EMPIRICAL
RELIABILITY:
0.5412
MARGINAL LATENT DISTRIBUTION(S)
===============================
MARGINAL LATENT DISTRIBUTION FOR TEST TEST0001
138
MEAN = -0.001
S.D. = 0.977
1
2
3
4
5
POINT -0.4000E+01 -0.3111E+01 -0.2222E+01 -0.1333E+01 -0.4444E+00
WEIGHT 0.3130E-04 0.1760E-02 0.2824E-01 0.1536E+00 0.3229E+00
6
7
8
9
10
POINT 0.4444E+00 0.1333E+01 0.2222E+01 0.3111E+01 0.4000E+01
WEIGHT 0.3106E+00 0.1474E+00 0.3240E-01 0.2929E-02 0.9992E-04
IN PHASE-3
IN PHASE-3
Outputs for 2 Parameter model are:
PH1
1
BILOG-MG V3.0
REV 19990104.1300
MODEL
DISTRIBUTED BY
CHICAGO, IL 60646
(800) 247-6113
(847) 675-0720
139
1
*** PHASE 1 ***
sample 20 by 76
>GLOBAL DFName = 'C:\drvn\new.dat',
NPArm = 2,
LOGistic,
SAVe;
===============================
SUBJECT DATA INPUT FILE C:\DRVN\NEW.DAT
CF.DAT
IF.DAT
140
CASE WEIGHTING
SF.DAT
NONE EMPLOYED
ITEM RESPONSE MODEL
>SAVE MASter = 'new.MAS',
CALib = 'new.CAL',
PARm = 'new.PAR',
SCOre = 'new.SCO',
COVariance = 'new.COV',
TSTat = 'new.TST',
ISTat = 'new.IST';
BILOG-MG SAVE FILES
[OUTPUT FILES]
BILOG-MG MASTER BINARY DATA NEW.MAS
CALIBRATION BINARY DATA FILENEW.CAL
CLASSICAL ITEM STATISTICS NEW.IST
NEW.PAR
NEW.SCO
ESTIMATED COVARIANCE FILE NEW.COV
141
NEW.TST
==========================
MAIN TEST LENGTHS:
20
>INPUT NTOtal = 20,
NALt = 3,
NIDchar = 4;
=========================
1
20
3
4
NUMBER OF GROUPS
1
1
TYPE OF DATA
142
>ITEMS ;
TEST SPECIFICATIONS
===================
INUmber = (1(1)20);
NUMBER OF ITEMS: 20
ITEM ITEM
ITEM ITEM
ITEM ITEM
ITEM ITEM
NUMBER NAME
NUMBER
NAME
----------------------------------------------------------------------1 ITEM0001
7 ITEM0007
13 ITEM0013 19 ITEM0019
2 ITEM0002
8 ITEM0008
14 ITEM0014 20 ITEM0020
3 ITEM0003
9 ITEM0009 15 ITEM0015
4 ITEM0004 10 ITEM0010 16 ITEM0016
5 ITEM0005 11 ITEM0011 17 ITEM0017
6 ITEM0006 12 ITEM0012 18 ITEM0018
-----------------------------------------------------------------------
FORM SPECIFICATIONS
143
===================
(4A1, 20A1)
OBSERVATION #
1 WEIGHT:
1.0000 ID : Ex01
GROUP #: 1
TRIED RIGHT
20.000 18.000
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0
OBSERVATION #
2 WEIGHT:
1.0000 ID : Ex02
GROUP #: 1
144
TRIED RIGHT
20.000 18.000
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 1.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0
76 OBSERVATIONS READ FROM FILE: C:\DRVN\NEW.DAT
76 OBSERVATIONS WRITTEN TO FILE: NEW.MAS
ITEM NAME
#TRIED #RIGHT PCT
------------------------------------------------------------------------1 ITEM0001 76.0 43.0 56.6 -0.26 0.366 0.462
2 ITEM0002 76.0 66.0 86.8 -1.89 0.116 0.184
3 ITEM0003 76.0 56.0 73.7 -1.03 0.212 0.286
4 ITEM0004 76.0 60.0 78.9 -1.32 0.089 0.125
5 ITEM0005 76.0 28.0 36.8 0.54 0.213 0.272
6 ITEM0006 76.0 61.0 80.3 -1.40 0.238 0.341
7 ITEM0007 76.0 64.0 84.2 -1.67 0.222 0.335
8 ITEM0008 76.0 47.0 61.8 -0.48 0.320 0.408
9 ITEM0009 76.0 41.0 53.9 -0.16 -0.019 -0.024
10 ITEM0010 76.0 35.0 46.1 0.16 0.430 0.539
11 ITEM0011 76.0 34.0 44.7 0.21 0.341 0.429
12 ITEM0012 76.0 46.0 60.5 -0.43 0.303 0.385
13 ITEM0013 76.0 63.0 82.9 -1.58 0.099 0.146
14 ITEM0014 76.0 39.0 51.3 -0.05 0.074 0.093
15 ITEM0015 76.0 57.0 75.0 -1.10 0.141 0.192
145
16 ITEM0016 76.0 54.0 71.1 -0.90 0.019 0.025
17 ITEM0017 76.0 70.0 92.1 -2.46 0.049 0.089
18 ITEM0018 76.0 59.0 77.6 -1.24 0.009 0.013
19 ITEM0019 76.0 52.0 68.4 -0.77 0.039 0.051
20 ITEM0020 76.0
4.0 5.3 2.89 0.187 0.388
-------------------------------------------------------------------------
IN PHASE-1
IN PHASE-1
11/01/2011 11:36:29
PH2
1
BILOG-MG V3.0
REV 19990329.1300
MODEL
*** PHASE 2 ***
sample 20 by 76
146
>CALIB ACCel = 1.0000,
TPRior;
======================
20
0.0100
1.0000
2
NO
DATA HANDLING:
YES
CONSTRAINT DISTRIBUTION ON THRESHOLDS: YES
SOURCE OF ITEM CONSTRAINT DISTIBUTION
MEANS AND STANDARD DEVIATIONS:
PROGRAM DEFAULTS
1
--------------------------------------------------------------------------------
******************************
TEST0001
******************************
METHOD OF SOLUTION:
147
1
2
3
4
5
POINT -0.4000E+01 -0.3429E+01 -0.2857E+01 -0.2286E+01 -0.1714E+01
WEIGHT 0.7648E-04 0.6387E-03 0.3848E-02 0.1673E-01 0.5245E-01
6
7
8
9
10
POINT -0.1143E+01 -0.5714E+00 -0.8882E-15 0.5714E+00 0.1143E+01
WEIGHT 0.1186E+00 0.1936E+00 0.2280E+00 0.1936E+00 0.1186E+00
11
12
13
14
15
POINT 0.1714E+01 0.2286E+01 0.2857E+01 0.3429E+01 0.4000E+01
WEIGHT 0.5245E-01 0.1673E-01 0.3848E-02 0.6387E-03 0.7648E-04
CONSTRAINT DISTRIBUTIONS ON ITEM PARAMETERS
(THRESHOLDS, NORMAL; SLOPES, LOG-NORMAL; GUESSING, BETA)
THRESHOLDS
SLOPES
ASYMPTOTES
ITEM
MU SIGMA MU SIGMA ALPHA
BETA
---------------------------------------------------------------------ITEM0001 0.000 2.000 1.000 1.649
ITEM0002 0.000 2.000 1.000 1.649
ITEM0003 0.000 2.000 1.000 1.649
ITEM0004 0.000 2.000 1.000 1.649
ITEM0005 0.000 2.000 1.000 1.649
ITEM0006 0.000 2.000 1.000 1.649
ITEM0007 0.000 2.000 1.000 1.649
ITEM0008 0.000 2.000 1.000 1.649
ITEM0009 0.000 2.000 1.000 1.649
ITEM0010 0.000 2.000 1.000 1.649
ITEM0011 0.000 2.000 1.000 1.649
148
ITEM0012 0.000 2.000 1.000 1.649
ITEM0013 0.000 2.000 1.000 1.649
ITEM0014 0.000 2.000 1.000 1.649
ITEM0015 0.000 2.000 1.000 1.649
ITEM0016 0.000 2.000 1.000 1.649
ITEM0017 0.000 2.000 1.000 1.649
ITEM0018 0.000 2.000 1.000 1.649
ITEM0019 0.000 2.000 1.000 1.649
ITEM0020 0.000 2.000 1.000 1.649
----------------------------------------------------------------------
[E-M CYCLES]
-2 LOG LIKELIHOOD =
CYCLE
-2 LOG LIKELIHOOD =
CYCLE
1642.233
-2 LOG LIKELIHOOD =
CYCLE
1674.291
-2 LOG LIKELIHOOD =
CYCLE
1634.645
1641.935
-2 LOG LIKELIHOOD =
1641.618
149
CYCLE
-2 LOG LIKELIHOOD =
CYCLE
-2 LOG LIKELIHOOD =
CYCLE
1641.252
-2 LOG LIKELIHOOD =
CYCLE
1641.432
1641.169
[NEWTON CYCLES]
-2 LOG LIKELIHOOD:
CYCLE
1641.0781
---------------------------------------------------------------------------2. 7. 11. 17. 9. 10. 11. 5. 4.
----------------------------------------------------------------------------1.880 -1.351 -0.961 -0.497 0.086 0.502 0.995 1.577 1.904
150
---------------------------------------------------------------------------1
ITEM
CHISQ
DF
S.E.
S.E.
S.E.
S.E.
S.E. (PROB)
------------------------------------------------------------------------------ITEM0001 | 0.343 | 1.118 | -0.307 | 0.745 | 0.000 | 2.2 3.0
| 0.278* | 0.373* | 0.247* | 0.249* | 0.000* | (0.5261)
|
|
|
|
|
|
ITEM0002 | 1.955 | 0.677 | -2.887 | 0.561 | 0.000 | 0.3 3.0
| 0.347* | 0.256* | 1.072* | 0.212* | 0.000* | (0.9514)
|
|
|
|
|
|
ITEM0003 | 1.107 | 0.691 | -1.602 | 0.568 | 0.000 | 3.7 5.0
| 0.272* | 0.246* | 0.614* | 0.202* | 0.000* | (0.5962)
|
|
|
|
|
|
ITEM0004 | 1.343 | 0.558 | -2.409 | 0.487 | 0.000 | 4.1 4.0
| 0.278* | 0.192* | 0.921* | 0.168* | 0.000* | (0.3933)
|
|
|
|
|
|
ITEM0005 | -0.571 | 0.639 | 0.893 | 0.539 | 0.000 | 6.5 5.0
| 0.246* | 0.205* | 0.475* | 0.173* | 0.000* | (0.2583)
|
|
|
|
|
|
ITEM0006 | 1.564 | 0.839 | -1.865 | 0.643 | 0.000 | 1.7 4.0
| 0.330* | 0.325* | 0.649* | 0.249* | 0.000* | (0.7993)
|
|
|
|
|
|
ITEM0007 | 1.898 | 0.922 | -2.058 | 0.678 | 0.000 | 0.7 4.0
| 0.377* | 0.363* | 0.698* | 0.267* | 0.000* | (0.9486)
|
|
|
|
|
|
ITEM0008 | 0.567 | 0.901 | -0.629 | 0.669 | 0.000 | 2.6 5.0
| 0.267* | 0.295* | 0.313* | 0.219* | 0.000* | (0.7603)
|
|
|
|
|
|
ITEM0009 | 0.158 | 0.431 | -0.368 | 0.396 | 0.000 | 11.8 7.0
| 0.223* | 0.140* | 0.532* | 0.129* | 0.000* | (0.1070)
|
|
|
|
|
|
ITEM0010 | -0.204 | 1.549 | 0.132 | 0.840 | 0.000 | 2.9 3.0
| 0.318* | 0.578* | 0.206* | 0.313* | 0.000* | (0.4110)
|
|
|
|
|
|
ITEM0011 | -0.265 | 1.299 | 0.204 | 0.792 | 0.000 | 2.1 4.0
151
| 0.296* | 0.447* | 0.228* | 0.273* | 0.000* | (0.7260)
|
|
|
|
|
|
ITEM0012 | 0.543 | 1.110 | -0.490 | 0.743 | 0.000 | 5.4
| 0.282* | 0.338* | 0.262* | 0.226* | 0.000* | (0.2498)
|
|
|
|
|
|
ITEM0013 | 1.642 | 0.650 | -2.526 | 0.545 | 0.000 | 5.8
| 0.311* | 0.241* | 0.929* | 0.202* | 0.000* | (0.1237)
|
|
|
|
|
|
ITEM0014 | 0.057 | 0.548 | -0.104 | 0.480 | 0.000 | 3.6
| 0.231* | 0.175* | 0.422* | 0.154* | 0.000* | (0.8206)
|
|
|
|
|
|
ITEM0015 | 1.176 | 0.685 | -1.717 | 0.565 | 0.000 | 7.4
| 0.279* | 0.252* | 0.640* | 0.208* | 0.000* | (0.1933)
|
|
|
|
|
|
ITEM0016 | 0.909 | 0.510 | -1.780 | 0.455 | 0.000 | 3.4
| 0.249* | 0.168* | 0.745* | 0.150* | 0.000* | (0.7539)
|
|
|
|
|
|
ITEM0017 | 2.434 | 0.645 | -3.776 | 0.542 | 0.000 | 0.2
| 0.416* | 0.221* | 1.391* | 0.186* | 0.000* | (0.9083)
|
|
|
|
|
|
ITEM0018 | 1.229 | 0.479 | -2.567 | 0.432 | 0.000 | 9.1
| 0.267* | 0.158* | 1.022* | 0.143* | 0.000* | (0.1060)
|
|
|
|
|
|
ITEM0019 | 0.776 | 0.481 | -1.613 | 0.433 | 0.000 | 11.5
| 0.242* | 0.158* | 0.729* | 0.143* | 0.000* | (0.0742)
|
|
|
|
|
|
ITEM0020 | -3.171 | 0.994 | 3.188 | 0.705 | 0.000 | 0.1
| 0.766* | 0.476* | 1.145* | 0.337* | 0.000* | (0.0000)
------------------------------------------------------------------------------* STANDARD ERROR
4.0
3.0
7.0
5.0
6.0
2.0
5.0
6.0
0.0
85.1 85.0
(0.4763)
-------------------------------------------------------------------------------
PARAMETER
MEAN STN DEV
----------------------------------SLOPE
0.786 0.302
LOG(SLOPE) -0.304 0.358
152
THRESHOLD
-1.114 1.580
1
2
3
4
5
POINT
-0.4604E+01 -0.3957E+01 -0.3309E+01 -0.2662E+01 -0.2015E+01
POSTERIOR 0.3774E-06 0.1769E-04 0.4155E-03 0.4964E-02 0.3156E-01
6
7
8
9
10
POINT
-0.1367E+01 -0.7202E+00 -0.7292E-01 0.5743E+00 0.1222E+01
POSTERIOR 0.1115E+00 0.2162E+00 0.2448E+00 0.2006E+00 0.1219E+00
11
12
13
14
15
POINT
0.1869E+01 0.2516E+01 0.3163E+01 0.3811E+01 0.4458E+01
POSTERIOR 0.5125E-01 0.1415E-01 0.2420E-02 0.2512E-03 0.1603E-04
MEAN
S.D.
0.00000
1.00000
IN PHASE-2
IN PHASE-2
11/01/2011 11:36:29
PH3
1
BILOG-MG V3.0
153
MODEL
*** PHASE 3 ***
sample 20 by 76
>SCORE ;
INFORMATION
TYPE OF PRIOR:
NORMAL
NEW.SCO
TYPE OF RESCALING:
new.PH3
NONE REQUESTED
NONE REQUESTED
NONE REQUESTED
QUAD
TEST NAME POINTS
----------------------1 TEST0001 10
----------------------1
154
******************************
SCORING
******************************
=====================
1
2
3
4
5
POINT -0.4000E+01 -0.3111E+01 -0.2222E+01 -0.1333E+01 -0.4444E+00
WEIGHT 0.1190E-03 0.2805E-02 0.3002E-01 0.1458E+00 0.3213E+00
6
7
8
9
10
POINT 0.4444E+00 0.1333E+01 0.2222E+01 0.3111E+01 0.4000E+01
WEIGHT 0.3213E+00 0.1458E+00 0.3002E-01 0.2805E-02 0.1190E-03
MEAN
S.D.
1
0.0000
1.0000
MARGINAL
WEIGHT TEST TRIED RIGHT PERCENT ABILITY S.E. PROB
-------------------------------------------------------------------------1 Ex01
|
|
1.00 TEST0001 20 18 90.00 | 1.2232 0.6097 | 0.001092
155
1 Ex02
1.00 TEST0001
1 Ex03
1.00 TEST0001
1 Ex04
1.00 TEST0001
1 Ex05
1.00 TEST0001
1 Ex06
1.00 TEST0001
1 Ex07
1.00 TEST0001
1 Ex08
1.00 TEST0001
1 Ex09
1.00 TEST0001
1 Ex10
1.00 TEST0001
1 Ex11
1.00 TEST0001
1 Ex12
1.00 TEST0001
1 Ex13
1.00 TEST0001
1 Ex14
1.00 TEST0001
1 Ex15
1.00 TEST0001
1 Ex16
1.00 TEST0001
1 Ex17
1.00 TEST0001
1 Ex18
1.00 TEST0001
1 Ex19
1.00 TEST0001
1 Ex20
1.00 TEST0001
1 Ex21
1.00 TEST0001
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
|
18
|
18
|
18
|
17
|
17
|
17
|
17
|
16
|
16
|
16
|
16
|
16
|
15
|
15
|
15
|
15
|
15
|
15
|
15
|
15
90.00 |
90.00 |
90.00 |
85.00 |
85.00 |
85.00 |
85.00 |
80.00 |
80.00 |
80.00 |
80.00 |
80.00 |
75.00 |
75.00 |
75.00 |
75.00 |
75.00 |
75.00 |
75.00 |
75.00 |
|
1.4344
|
1.4647
|
1.4846
|
1.4594
|
0.8394
|
1.3879
|
1.2864
|
0.7548
|
1.1436
|
0.7687
|
0.5703
|
1.0215
|
0.2137
|
0.7928
|
0.1484
|
0.6674
|
0.4682
|
0.9277
|
0.3240
|
0.8965
0.6275 | 0.001022
0.6303 | 0.002013
0.6321 | 0.004018
0.6298 | 0.000059
0.5754 | 0.000453
0.6234 | 0.000003
0.6148 | 0.000799
0.5662 | 0.000240
0.6033 | 0.000000
0.5677 | 0.000348
0.5475 | 0.000550
0.5931 | 0.000774
0.5383 | 0.000020
0.5703 | 0.000038
0.5390 | 0.000175
0.5567 | 0.000094
0.5407 | 0.000028
0.5844 | 0.000084
0.5374 | 0.000059
0.5813 | 0.000145
156
1 Ex22
1.00 TEST0001
1 Ex23
1.00 TEST0001
1 Ex24
1.00 TEST0001
1 Ex25
1.00 TEST0001
1 Ex26
1.00 TEST0001
1 Ex27
1.00 TEST0001
1 Ex28
1.00 TEST0001
1 Ex29
1.00 TEST0001
1 Ex30
1.00 TEST0001
1 Ex31
1.00 TEST0001
1 Ex32
1.00 TEST0001
1 Ex33
1.00 TEST0001
1 Ex34
1.00 TEST0001
1 Ex35
1.00 TEST0001
1 Ex36
1.00 TEST0001
1 Ex37
1.00 TEST0001
1 Ex38
1.00 TEST0001
1 Ex39
1.00 TEST0001
1 Ex40
1.00 TEST0001
1 Ex41
1.00 TEST0001
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
|
15
|
15
|
15
|
15
|
14
|
14
|
14
|
14
|
14
|
14
|
14
|
13
|
13
|
13
|
13
|
13
|
13
|
13
|
13
|
13
75.00 |
75.00 |
75.00 |
75.00 |
70.00 |
70.00 |
70.00 |
70.00 |
70.00 |
70.00 |
70.00 |
65.00 |
65.00 |
65.00 |
65.00 |
65.00 |
65.00 |
65.00 |
65.00 |
65.00 |
|
0.6887
|
0.2848
|
0.8859
|
0.3557
|
0.5247
|
0.6647
|
0.6393
|
-0.1402
|
0.5608
|
0.1184
|
0.4719
|
0.0630
|
-0.3679
|
0.1148
|
-0.0654
|
0.1582
|
-0.2354
|
-0.3040
|
-0.1995
|
0.1748
0.5590 | 0.000211
0.5376 | 0.000591
0.5802 | 0.000194
0.5376 | 0.000026
0.5440 | 0.000083
0.5565 | 0.000035
0.5539 | 0.000020
0.5311 | 0.000112
0.5467 | 0.000000
0.5391 | 0.000157
0.5409 | 0.000040
0.5389 | 0.000037
0.5177 | 0.000048
0.5391 | 0.000007
0.5352 | 0.000002
0.5389 | 0.000005
0.5247 | 0.000014
0.5205 | 0.000043
0.5272 | 0.000003
0.5388 | 0.000031
157
1 Ex42
1.00 TEST0001
1 Ex43
1.00 TEST0001
1 Ex44
1.00 TEST0001
1 Ex45
1.00 TEST0001
1 Ex46
1.00 TEST0001
1 Ex47
1.00 TEST0001
1 Ex48
1.00 TEST0001
1 Ex49
1.00 TEST0001
1 Ex50
1.00 TEST0001
1 Ex51
1.00 TEST0001
1 Ex52
1.00 TEST0001
1 Ex53
1.00 TEST0001
1 Ex54
1.00 TEST0001
1 Ex55
1.00 TEST0001
1 Ex56
1.00 TEST0001
1 Ex57
1.00 TEST0001
1 Ex58
1.00 TEST0001
1 Ex59
1.00 TEST0001
1 Ex60
1.00 TEST0001
1 Ex61
1.00 TEST0001
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
|
13
|
13
|
12
|
12
|
12
|
12
|
12
|
12
|
12
|
11
|
11
|
11
|
11
|
11
|
11
|
11
|
11
|
11
|
11
|
11
65.00 |
65.00 |
60.00 |
60.00 |
60.00 |
60.00 |
60.00 |
60.00 |
60.00 |
55.00 |
55.00 |
55.00 |
55.00 |
55.00 |
55.00 |
55.00 |
55.00 |
55.00 |
55.00 |
55.00 |
|
-0.2231
|
0.0039
|
0.3065
|
-0.5852
|
-0.4774
|
-0.4110
|
-0.3277
|
-0.4108
|
0.2843
|
-0.7692
|
-0.3068
|
-0.7090
|
-0.4841
|
-0.5375
|
-0.5135
|
-0.3147
|
-0.4706
|
-0.6986
|
-0.3693
|
-0.5523
0.5256 | 0.000001
0.5378 | 0.000015
0.5375 | 0.000001
0.5216 | 0.000026
0.5170 | 0.000005
0.5167 | 0.000027
0.5193 | 0.000011
0.5167 | 0.000008
0.5376 | 0.000006
0.5352 | 0.000016
0.5204 | 0.000004
0.5307 | 0.000258
0.5171 | 0.000004
0.5190 | 0.000001
0.5180 | 0.000024
0.5199 | 0.000002
0.5168 | 0.000006
0.5299 | 0.000107
0.5176 | 0.000001
0.5197 | 0.000003
158
1 Ex62
|
|
1.00 TEST0001 20 10 50.00 | -0.9106 0.5428 | 0.000017
1 Ex63
|
|
1.00 TEST0001 20 10 50.00 | -0.7928 0.5368 | 0.000011
1 Ex64
|
|
1.00 TEST0001 20 10 50.00 | -0.7962 0.5370 | 0.000001
1 Ex65
|
|
1.00 TEST0001 20 10 50.00 | -0.4776 0.5170 | 0.000000
1 Ex66
|
|
1.00 TEST0001 20 10 50.00 | -0.7374 0.5329 | 0.000020
1 Ex67
|
|
1.00 TEST0001 20 9 45.00 | -0.9975 0.5450 | 0.000111
1 Ex68
|
|
1.00 TEST0001 20 9 45.00 | -1.0636 0.5456 | 0.000003
1 Ex69
|
|
1.00 TEST0001 20 9 45.00 | -0.9975 0.5450 | 0.000111
1 Ex70
|
|
1.00 TEST0001 20 9 45.00 | -0.9975 0.5450 | 0.000111
1 Ex71
|
|
1.00 TEST0001 20 9 45.00 | -0.9909 0.5449 | 0.000015
1 Ex72
|
|
1.00 TEST0001 20 9 45.00 | -0.9520 0.5441 | 0.000000
1 Ex73
|
|
1.00 TEST0001 20 8 40.00 | -1.2361 0.5459 | 0.000001
1 Ex74
|
|
1.00 TEST0001 20 8 40.00 | -1.2186 0.5458 | 0.000004
1 Ex75
|
|
1.00 TEST0001 20 7 35.00 | -1.6000 0.5634 | 0.000001
1 Ex76
|
|
1.00 TEST0001 20 6 30.00 | -1.4811 0.5550 | 0.000001
--------------------------------------------------------------------------
======================================
159
TEST0001
TEST0001
1.0000
TEST:
TEST0001
MEAN:
0.0113
S.D.:
0.7775
VARIANCE:
0.6045
TEST:
TEST0001
RMS:
0.5495
VARIANCE:
0.3019
EMPIRICAL
RELIABILITY:
0.6669
===============================
MEAN = 0.011
S.D. = 0.924
1
2
3
4
5
POINT -0.4000E+01 -0.3111E+01 -0.2222E+01 -0.1333E+01 -0.4444E+00
WEIGHT 0.3965E-05 0.5503E-03 0.1765E-01 0.1480E+00 0.3457E+00
6
7
8
9
10
POINT 0.4444E+00 0.1333E+01 0.2222E+01 0.3111E+01 0.4000E+01
WEIGHT 0.3111E+00 0.1464E+00 0.2863E-01 0.1943E-02 0.4271E-04
160
IN PHASE-3
IN PHASE-3
PH1
1
BILOG-MG V3.0
REV 19990104.1300
MODEL
DISTRIBUTED BY
CHICAGO, IL 60646
(800) 247-6113
(847) 675-0720
1
*** PHASE 1 ***
161
sample 20 by 76
>GLOBAL DFName = 'C:\drvn\test2.dat',
NPArm = 3,
LOGistic,
SAVe;
===============================
SUBJECT DATA INPUT FILE C:\DRVN\TEST2.DAT
CF.DAT
IF.DAT
CASE WEIGHTING
SF.DAT
NONE EMPLOYED
ITEM RESPONSE MODEL
>SAVE MASter = 'neha.MAS',
162
CALib = 'neha.CAL',
PARm = 'neha.PAR',
SCOre = 'neha.SCO',
COVariance = 'neha.COV',
TSTat = 'neha.TST',
ISTat = 'neha.IST';
BILOG-MG SAVE FILES
[OUTPUT FILES]
BILOG-MG MASTER BINARY DATA NEHA.MAS
CALIBRATION BINARY DATA FILENEHA.CAL
CLASSICAL ITEM STATISTICS NEHA.IST
NEHA.PAR
NEHA.SCO
ESTIMATED COVARIANCE FILE NEHA.COV
NEHA.TST
==========================
163
MAIN TEST LENGTHS:
20
>INPUT NTOtal = 20,
NALt = 3,
NIDchar = 10;
=========================
1
20
3
10
NUMBER OF GROUPS
1
1
TYPE OF DATA
>ITEMS ;
TEST SPECIFICATIONS
===================
164
INUmber = (1(1)20);
NUMBER OF ITEMS: 20
ITEM ITEM
ITEM ITEM
ITEM ITEM
ITEM ITEM
NUMBER NAME
NUMBER
NAME
----------------------------------------------------------------------1 ITEM0001
7 ITEM0007
13 ITEM0013 19 ITEM0019
2 ITEM0002
8 ITEM0008
14 ITEM0014 20 ITEM0020
3 ITEM0003
9 ITEM0009 15 ITEM0015
4 ITEM0004 10 ITEM0010 16 ITEM0016
5 ITEM0005 11 ITEM0011 17 ITEM0017
6 ITEM0006 12 ITEM0012 18 ITEM0018
-----------------------------------------------------------------------
FORM SPECIFICATIONS
===================
(10A1, 20A1)
165
OBSERVATION #
1 WEIGHT:
GROUP #: 1
TRIED RIGHT
20.000 18.000
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0
OBSERVATION #
2 WEIGHT:
GROUP #: 1
TRIED RIGHT
20.000 18.000
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 1.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
166
RIGHT 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0
76 OBSERVATIONS READ FROM FILE: C:\DRVN\TEST2.DAT
76 OBSERVATIONS WRITTEN TO FILE: NEHA.MAS
ITEM NAME
#TRIED #RIGHT PCT
------------------------------------------------------------------------1 ITEM0001 76.0 43.0 56.6 -0.26 0.366 0.462
2 ITEM0002 76.0 66.0 86.8 -1.89 0.116 0.184
3 ITEM0003 76.0 56.0 73.7 -1.03 0.212 0.286
4 ITEM0004 76.0 60.0 78.9 -1.32 0.089 0.125
5 ITEM0005 76.0 28.0 36.8 0.54 0.213 0.272
6 ITEM0006 76.0 61.0 80.3 -1.40 0.238 0.341
7 ITEM0007 76.0 64.0 84.2 -1.67 0.222 0.335
8 ITEM0008 76.0 47.0 61.8 -0.48 0.320 0.408
9 ITEM0009 76.0 41.0 53.9 -0.16 -0.019 -0.024
10 ITEM0010 76.0 35.0 46.1 0.16 0.430 0.539
11 ITEM0011 76.0 34.0 44.7 0.21 0.341 0.429
12 ITEM0012 76.0 46.0 60.5 -0.43 0.303 0.385
13 ITEM0013 76.0 63.0 82.9 -1.58 0.099 0.146
14 ITEM0014 76.0 39.0 51.3 -0.05 0.074 0.093
15 ITEM0015 76.0 57.0 75.0 -1.10 0.141 0.192
16 ITEM0016 76.0 54.0 71.1 -0.90 0.019 0.025
17 ITEM0017 76.0 70.0 92.1 -2.46 0.049 0.089
18 ITEM0018 76.0 59.0 77.6 -1.24 0.009 0.013
19 ITEM0019 76.0 52.0 68.4 -0.77 0.039 0.051
20 ITEM0020 76.0
4.0 5.3 2.89 0.187 0.388
-------------------------------------------------------------------------
IN PHASE-1
167
IN PHASE-1
11/01/2011 12:51:42
PH2
1
BILOG-MG V3.0
REV 19990329.1300
MODEL
*** PHASE 2 ***
sample 20 by 76
TPRior,
GPRior;
======================
168
20
0.0100
1.0000
2
NO
DATA HANDLING:
CONSTRAINT DISTRIBUTION ON ASYMPTOTES: YES
YES
PROGRAM DEFAULTS
1
--------------------------------------------------------------------------------
******************************
TEST0001
******************************
METHOD OF SOLUTION:
1
2
3
4
5
169
POINT -0.4000E+01 -0.3429E+01 -0.2857E+01 -0.2286E+01 -0.1714E+01
WEIGHT 0.7648E-04 0.6387E-03 0.3848E-02 0.1673E-01 0.5245E-01
6
7
8
9
10
POINT -0.1143E+01 -0.5714E+00 -0.8882E-15 0.5714E+00 0.1143E+01
WEIGHT 0.1186E+00 0.1936E+00 0.2280E+00 0.1936E+00 0.1186E+00
11
12
13
14
15
POINT 0.1714E+01 0.2286E+01 0.2857E+01 0.3429E+01 0.4000E+01
WEIGHT 0.5245E-01 0.1673E-01 0.3848E-02 0.6387E-03 0.7648E-04
THRESHOLDS
SLOPES
ASYMPTOTES
ITEM
BETA
---------------------------------------------------------------------ITEM0001 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0002 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0003 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0004 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0005 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0006 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0007 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0008 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0009 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0010 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0011 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0012 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0013 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0014 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0015 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0016 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0017 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0018 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0019 0.000 2.000 1.000 1.649
7.67 14.33
170
ITEM0020 0.000 2.000 1.000 1.649
7.67 14.33
----------------------------------------------------------------------
[E-M CYCLES]
-2 LOG LIKELIHOOD =
CYCLE
-2 LOG LIKELIHOOD =
CYCLE
1644.191
-2 LOG LIKELIHOOD =
CYCLE
1643.897
-2 LOG LIKELIHOOD =
CYCLE
1643.966
-2 LOG LIKELIHOOD =
CYCLE
1648.773
-2 LOG LIKELIHOOD =
CYCLE
1682.402
1643.838
171
-2 LOG LIKELIHOOD =
CYCLE
-2 LOG LIKELIHOOD =
CYCLE
1643.870
-2 LOG LIKELIHOOD =
CYCLE
1643.905
-2 LOG LIKELIHOOD =
CYCLE
1644.061
1643.867
[NEWTON CYCLES]
-2 LOG LIKELIHOOD:
1643.8586
CYCLE 11; LARGEST CHANGE= 0.00306
---------------------------------------------------------------------------0. 2. 8. 17. 14. 12. 10. 7. 6.
172
---------------------------------------------------------------------------******* -1.947 -1.308 -0.777 -0.334 0.271 0.879 1.292 1.861
---------------------------------------------------------------------------1
ITEM
CHISQ
DF
S.E.
S.E.
S.E.
S.E.
S.E. (PROB)
------------------------------------------------------------------------------ITEM0001 | -0.570 | 1.455 | 0.392 | 0.824 | 0.295 | 2.3 5.0
| 0.649* | 0.690* | 0.402* | 0.391* | 0.090* | (0.8053)
|
|
|
|
|
|
ITEM0002 | 1.462 | 0.830 | -1.762 | 0.639 | 0.352 | 0.9 3.0
| 0.458* | 0.329* | 0.791* | 0.254* | 0.107* | (0.8347)
|
|
|
|
|
|
ITEM0003 | 0.466 | 0.888 | -0.525 | 0.664 | 0.339 | 12.1 5.0
| 0.450* | 0.348* | 0.554* | 0.261* | 0.103* | (0.0337)
|
|
|
|
|
|
ITEM0004 | 0.699 | 0.651 | -1.075 | 0.545 | 0.361 | 3.2 4.0
| 0.419* | 0.234* | 0.768* | 0.196* | 0.106* | (0.5292)
|
|
|
|
|
|
ITEM0005 | -2.009 | 1.090 | 1.844 | 0.737 | 0.271 | 9.6 5.0
| 0.928* | 0.513* | 0.828* | 0.347* | 0.073* | (0.0867)
|
|
|
|
|
|
ITEM0006 | 1.164 | 1.282 | -0.908 | 0.788 | 0.327 | 1.4 3.0
| 0.542* | 0.612* | 0.460* | 0.376* | 0.103* | (0.7154)
|
|
|
|
|
|
ITEM0007 | 1.417 | 1.096 | -1.292 | 0.739 | 0.335 | 2.1 3.0
| 0.502* | 0.466* | 0.577* | 0.314* | 0.105* | (0.5547)
|
|
|
|
|
|
ITEM0008 | -0.201 | 1.417 | 0.142 | 0.817 | 0.305 | 3.7 5.0
| 0.579* | 0.646* | 0.395* | 0.372* | 0.094* | (0.5960)
|
|
|
|
|
|
ITEM0009 | -1.136 | 0.587 | 1.936 | 0.506 | 0.374 | 6.0 6.0
| 0.658* | 0.223* | 1.195* | 0.192* | 0.091* | (0.4187)
|
|
|
|
|
|
ITEM0010 | -1.143 | 1.894 | 0.603 | 0.884 | 0.236 | 2.8 4.0
| 0.861* | 1.085* | 0.333* | 0.507* | 0.076* | (0.5896)
173
|
|
|
|
|
|
ITEM0011 | -1.205 | 1.704 | 0.707 | 0.862 | 0.237 | 2.7
| 0.820* | 0.903* | 0.359* | 0.457* | 0.076* | (0.7520)
|
|
|
|
|
|
ITEM0012 | -0.332 | 1.316 | 0.253 | 0.796 | 0.310 | 4.9
| 0.595* | 0.533* | 0.424* | 0.323* | 0.094* | (0.4257)
|
|
|
|
|
|
ITEM0013 | 1.107 | 0.853 | -1.297 | 0.649 | 0.353 | 1.1
| 0.449* | 0.339* | 0.670* | 0.258* | 0.107* | (0.8939)
|
|
|
|
|
|
ITEM0014 | -1.106 | 0.870 | 1.272 | 0.656 | 0.331 | 6.4
| 0.684* | 0.357* | 0.750* | 0.270* | 0.090* | (0.3793)
|
|
|
|
|
|
ITEM0015 | 0.544 | 1.000 | -0.544 | 0.707 | 0.347 | 3.3
| 0.476* | 0.416* | 0.514* | 0.294* | 0.105* | (0.5025)
|
|
|
|
|
|
ITEM0016 | 0.113 | 0.604 | -0.188 | 0.517 | 0.369 | 3.8
| 0.451* | 0.217* | 0.760* | 0.185* | 0.104* | (0.5783)
|
|
|
|
|
|
ITEM0017 | 1.980 | 0.723 | -2.737 | 0.586 | 0.353 | 0.3
| 0.486* | 0.258* | 1.148* | 0.209* | 0.107* | (0.8562)
|
|
|
|
|
|
ITEM0018 | 0.600 | 0.587 | -1.021 | 0.507 | 0.359 | 4.4
| 0.410* | 0.206* | 0.821* | 0.178* | 0.106* | (0.3492)
|
|
|
|
|
|
ITEM0019 | -0.074 | 0.554 | 0.133 | 0.485 | 0.371 | 6.2
| 0.461* | 0.197* | 0.825* | 0.172* | 0.103* | (0.4032)
|
|
|
|
|
|
ITEM0020 | -3.711 | 0.886 | 4.190 | 0.663 | 0.097 | 5.3
| 1.227* | 0.409* | 2.078* | 0.306* | 0.034* | (0.0000)
------------------------------------------------------------------------------* STANDARD ERROR
5.0
5.0
4.0
6.0
4.0
5.0
2.0
4.0
6.0
0.0
82.4 84.0
(0.5275)
-------------------------------------------------------------------------------
PARAMETER
MEAN STN DEV
----------------------------------174
ASYMPTOTE 0.316 0.066
SLOPE
1.014 0.388
LOG(SLOPE) -0.052 0.371
THRESHOLD 0.006 1.539
1
2
3
4
5
POINT
-0.4111E+01 -0.3524E+01 -0.2937E+01 -0.2349E+01 -0.1762E+01
POSTERIOR 0.4869E-04 0.4659E-03 0.3089E-02 0.1450E-01 0.4928E-01
6
7
8
9
10
POINT
-0.1175E+01 -0.5872E+00 0.1730E-03 0.5876E+00 0.1175E+01
POSTERIOR 0.1221E+00 0.2064E+00 0.2232E+00 0.1845E+00 0.1221E+00
11
12
13
14
15
POINT
0.1762E+01 0.2350E+01 0.2937E+01 0.3524E+01 0.4112E+01
POSTERIOR 0.5450E-01 0.1610E-01 0.3128E-02 0.3896E-03 0.3071E-04
MEAN
S.D.
0.00000
1.00000
IN PHASE-2
IN PHASE-2
11/01/2011 12:51:42
PH3
1
175
BILOG-MG V3.0
MODEL
*** PHASE 3 ***
sample 20 by 76
>SCORE ;
INFORMATION
TYPE OF PRIOR:
NORMAL
NEHA.SCO
TYPE OF RESCALING:
neha.PH3
NONE REQUESTED
NONE REQUESTED
NONE REQUESTED
QUAD
TEST NAME POINTS
----------------------176
1 TEST0001 10
----------------------1
******************************
SCORING
******************************
=====================
1
2
3
4
5
POINT -0.4000E+01 -0.3111E+01 -0.2222E+01 -0.1333E+01 -0.4444E+00
WEIGHT 0.1190E-03 0.2805E-02 0.3002E-01 0.1458E+00 0.3213E+00
6
7
8
9
10
POINT 0.4444E+00 0.1333E+01 0.2222E+01 0.3111E+01 0.4000E+01
WEIGHT 0.3213E+00 0.1458E+00 0.3002E-01 0.2805E-02 0.1190E-03
MEAN
S.D.
1
0.0000
1.0000
WEIGHT TEST TRIED RIGHT PERCENT
MARGINAL
ABILITY S.E. PROB
177
-------------------------------------------------------------------------1 Examinee01
|
|
1.00 TEST0001 20 18 90.00 | 1.3195 0.6098 | 0.001078
1 Examinee02
|
|
1.00 TEST0001 20 18 90.00 | 1.5528 0.6315 | 0.000934
1 Examinee03
|
|
1.00 TEST0001 20 18 90.00 | 1.6072 0.6332 | 0.002110
1 Examinee04
|
|
1.00 TEST0001 20 18 90.00 | 1.6352 0.6304 | 0.004593
1 Examinee05
|
|
1.00 TEST0001 20 17 85.00 | 1.3368 0.6183 | 0.000085
1 Examinee06
|
|
1.00 TEST0001 20 17 85.00 | 0.7711 0.5812 | 0.000317
1 Examinee07
|
|
1.00 TEST0001 20 17 85.00 | 1.2016 0.6307 | 0.000003
1 Examinee08
|
|
1.00 TEST0001 20 17 85.00 | 1.4298 0.6138 | 0.000902
1 Examinee09
|
|
1.00 TEST0001 20 16 80.00 | 0.8595 0.5835 | 0.000267
1 Examinee10
|
|
1.00 TEST0001 20 16 80.00 | 0.8747 0.6472 | 0.000000
1 Examinee11
|
|
1.00 TEST0001 20 16 80.00 | 0.8124 0.5733 | 0.000307
1 Examinee12
|
|
1.00 TEST0001 20 16 80.00 | 0.6021 0.5502 | 0.000539
1 Examinee13
|
|
1.00 TEST0001 20 16 80.00 | 1.1091 0.5790 | 0.000806
1 Examinee14
|
|
1.00 TEST0001 20 15 75.00 | 0.2114 0.5729 | 0.000018
1 Examinee15
|
|
1.00 TEST0001 20 15 75.00 | 0.8054 0.6002 | 0.000029
1 Examinee16
|
|
1.00 TEST0001 20 15 75.00 | 0.2354 0.5341 | 0.000190
1 Examinee17
|
|
1.00 TEST0001 20 15 75.00 | 0.7558 0.5897 | 0.000104
1 Examinee18
|
|
1.00 TEST0001 20 15 75.00 | 0.3469 0.5883 | 0.000023
1 Examinee19
|
|
1.00 TEST0001 20 15 75.00 | 1.0268 0.6009 | 0.000087
1 Examinee20
|
|
178
1.00 TEST0001
1 Examinee21
1.00 TEST0001
1 Examinee22
1.00 TEST0001
1 Examinee23
1.00 TEST0001
1 Examinee24
1.00 TEST0001
1 Examinee25
1.00 TEST0001
1 Examinee26
1.00 TEST0001
1 Examinee27
1.00 TEST0001
1 Examinee28
1.00 TEST0001
1 Examinee29
1.00 TEST0001
1 Examinee30
1.00 TEST0001
1 Examinee31
1.00 TEST0001
1 Examinee32
1.00 TEST0001
1 Examinee33
1.00 TEST0001
1 Examinee34
1.00 TEST0001
1 Examinee35
1.00 TEST0001
1 Examinee36
1.00 TEST0001
1 Examinee37
1.00 TEST0001
1 Examinee38
1.00 TEST0001
1 Examinee39
1.00 TEST0001
1 Examinee40
20
15
20
15
20
15
20
15
20
15
20
15
20
14
20
14
20
14
20
14
20
14
20
14
20
14
20
13
20
13
20
13
20
13
20
13
20
13
20
13
75.00 |
|
75.00 |
|
75.00 |
|
75.00 |
|
75.00 |
|
75.00 |
|
70.00 |
|
70.00 |
|
70.00 |
|
70.00 |
|
70.00 |
|
70.00 |
|
70.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
0.2787
|
1.0147
|
0.7744
|
0.3820
|
1.0212
|
0.3172
|
0.4626
|
0.7006
|
0.6856
|
0.0081
|
-0.0043
|
0.2261
|
0.4884
|
0.0464
|
-0.3784
|
-0.0417
|
-0.3141
|
-0.0286
|
-0.2634
|
-0.3076
|
0.5630 | 0.000057
0.5893 | 0.000155
0.5802 | 0.000238
0.5165 | 0.000611
0.5870 | 0.000229
0.5952 | 0.000026
0.5858 | 0.000073
0.6039 | 0.000033
0.6088 | 0.000020
0.5471 | 0.000120
0.6800 | 0.000000
0.5395 | 0.000156
0.5897 | 0.000042
0.5826 | 0.000039
0.5610 | 0.000042
0.6291 | 0.000006
0.6351 | 0.000003
0.6220 | 0.000005
0.5840 | 0.000013
0.5547 | 0.000044
179
1.00 TEST0001
1 Examinee41
1.00 TEST0001
1 Examinee42
1.00 TEST0001
1 Examinee43
1.00 TEST0001
1 Examinee44
1.00 TEST0001
1 Examinee45
1.00 TEST0001
1 Examinee46
1.00 TEST0001
1 Examinee47
1.00 TEST0001
1 Examinee48
1.00 TEST0001
1 Examinee49
1.00 TEST0001
1 Examinee50
1.00 TEST0001
1 Examinee51
1.00 TEST0001
1 Examinee52
1.00 TEST0001
1 Examinee53
1.00 TEST0001
1 Examinee54
1.00 TEST0001
1 Examinee55
1.00 TEST0001
1 Examinee56
1.00 TEST0001
1 Examinee57
1.00 TEST0001
1 Examinee58
1.00 TEST0001
1 Examinee59
1.00 TEST0001
1 Examinee60
20
13
20
13
20
13
20
13
20
12
20
12
20
12
20
12
20
12
20
12
20
12
20
11
20
11
20
11
20
11
20
11
20
11
20
11
20
11
20
11
65.00 |
|
65.00 |
|
65.00 |
|
65.00 |
|
60.00 |
|
60.00 |
|
60.00 |
|
60.00 |
|
60.00 |
|
60.00 |
|
60.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
55.00 |
|
-0.4053
|
0.2244
|
-0.4945
|
0.0518
|
0.2068
|
-0.4505
|
-0.4045
|
-0.2474
|
-0.3041
|
-0.4160
|
0.2030
|
-0.7794
|
-0.4358
|
-0.4539
|
-0.6466
|
-0.8256
|
-0.3883
|
-0.6270
|
-0.4612
|
-0.4731
|
0.6106 | 0.000003
0.5755 | 0.000032
0.6475 | 0.000001
0.5898 | 0.000016
0.6733 | 0.000001
0.5682 | 0.000020
0.5801 | 0.000004
0.5664 | 0.000027
0.6019 | 0.000012
0.5926 | 0.000007
0.6213 | 0.000006
0.5830 | 0.000013
0.6184 | 0.000005
0.5201 | 0.000178
0.6155 | 0.000005
0.6263 | 0.000001
0.5776 | 0.000020
0.6613 | 0.000002
0.6121 | 0.000006
0.5313 | 0.000077
180
1.00 TEST0001 20 11 55.00 | -0.9057 0.6687 | 0.000001
1 Examinee61
|
|
1.00 TEST0001 20 11 55.00 | -0.6860 0.6222 | 0.000004
1 Examinee62
|
|
1.00 TEST0001 20 10 50.00 | -0.7320 0.5875 | 0.000010
1 Examinee63
|
|
1.00 TEST0001 20 10 50.00 | -0.7341 0.5850 | 0.000009
1 Examinee64
|
|
1.00 TEST0001 20 10 50.00 | -0.9089 0.6251 | 0.000001
1 Examinee65
|
|
1.00 TEST0001 20 10 50.00 | -1.1283 0.6851 | 0.000000
1 Examinee66
|
|
1.00 TEST0001 20 10 50.00 | -0.6220 0.5673 | 0.000016
1 Examinee67
|
|
1.00 TEST0001 20 9 45.00 | -0.6641 0.5397 | 0.000056
1 Examinee68
|
|
1.00 TEST0001 20 9 45.00 | -0.9952 0.6214 | 0.000002
1 Examinee69
|
|
1.00 TEST0001 20 9 45.00 | -0.6641 0.5397 | 0.000056
1 Examinee70
|
|
1.00 TEST0001 20 9 45.00 | -0.6641 0.5397 | 0.000056
1 Examinee71
|
|
1.00 TEST0001 20 9 45.00 | -0.9159 0.5938 | 0.000011
1 Examinee72
|
|
1.00 TEST0001 20 9 45.00 | -1.3222 0.6850 | 0.000000
1 Examinee73
|
|
1.00 TEST0001 20 8 40.00 | -1.1706 0.6255 | 0.000001
1 Examinee74
|
|
1.00 TEST0001 20 8 40.00 | -1.0727 0.6381 | 0.000002
1 Examinee75
|
|
1.00 TEST0001 20 7 35.00 | -1.5746 0.6272 | 0.000000
1 Examinee76
|
|
1.00 TEST0001 20 6 30.00 | -1.5867 0.6572 | 0.000001
--------------------------------------------------------------------------
======================================
181
TEST0001
TEST0001
1.0000
TEST:
TEST0001
MEAN:
0.0011
S.D.:
0.7947
VARIANCE:
0.6315
TEST:
TEST0001
RMS:
0.6000
VARIANCE:
0.3600
EMPIRICAL
RELIABILITY:
0.6369
===============================
MEAN = 0.001
S.D. = 0.969
1
2
3
4
5
POINT -0.4000E+01 -0.3111E+01 -0.2222E+01 -0.1333E+01 -0.4444E+00
WEIGHT 0.8552E-04 0.2271E-02 0.2701E-01 0.1472E+00 0.3358E+00
6
7
8
9
10
182
POINT 0.4444E+00 0.1333E+01 0.2222E+01 0.3111E+01 0.4000E+01
WEIGHT 0.3007E+00 0.1540E+00 0.3061E-01 0.2219E-02 0.5505E-04
IN PHASE-3
IN PHASE-3
2PM BILOG CURVES
a = 1.118
b = -0.307
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 1
183
a = 0.677
b = -2.887
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 2
184
a = 0.691
b = -1.602
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
1
2
3
Scale Score
Ability
0
Item: 3
185
a = 0.558
b = -2.409
1.0
0.6
0.5
0.8
Info rmatio n
Pro bab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 4
186
a = 0.639
b = 0.893
1.0
0.6
0.5
0.8
In fo r m a tio n
P r o b a b ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 5
187
a = 0.839
b = -1.865
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 6
188
a = 0.922
b = -2.058
1.0
0.6
0.5
0.8
In fo r m a tio n
P r o b a b ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 7
189
a = 0.901
b = -0.629
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 8
190
a = 0.431
b = -0.368
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 9
191
a = 1.549
b = 0.132
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b a b ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 10
192
a = 1.299
b = 0.204
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 11
193
a = 1.110
b = -0.490
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 12
194
a = 0.650
b = -2.526
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 13
195
a = 0.548
b = -0.104
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 14
196
a = 0.685
b = -1.717
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 15
197
a = 0.510
b = -1.780
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 16
198
a = 0.645
b = -3.776
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
0
-3
-2
-1
0
1
2
0
-3
3
-2
-1
0
Ability
1
2
3
Scale Score
Item: 17
a = 0.479
b = -2.567
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 18
199
a = 0.481
b = -1.613
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 19
200
a = 0.994
b = 3.188
1.0
0.6
0.5
0.8
In fo r m atio n
P r o b ab ility
0.4
0.6
0.4
0.3
0.2
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 20
Test of 25 items administered on random sample of 1000 test takers in the domain of
Analytical Ability
Outputs for a Single Parameter model are:
PH1
1
BILOG-MG V3.0
REV 19990104.1300
201
MODEL
DISTRIBUTED BY
CHICAGO, IL 60646
(800) 247-6113
(847) 675-0720
1
*** PHASE 1 ***
25 by 1000
---> FIND WARNING: 2 RECORDS NOT CONTAINING > IN COLUMN 1 HAVE
BEEN SKIPPED
>GLOBAL DFName = 'C:\25by1000\RG.dat',
NPArm = 1,
LOGistic,
202
SAVe;
===============================
SUBJECT DATA INPUT FILE C:\25BY1000\RG.DAT
CF.DAT
IF.DAT
CASE WEIGHTING
SF.DAT
NONE EMPLOYED
ITEM RESPONSE MODEL
>SAVE MASter = 'RG1PM.MAS',
CALib = 'RG1PM.CAL',
PARm = 'RG1PM.PAR',
SCOre = 'RG1PM.SCO',
COVariance = 'RG1PM.COV',
TSTat = 'RG1PM.TST',
ISTat = 'RG1PM.IST';
203
BILOG-MG SAVE FILES
[OUTPUT FILES]
BILOG-MG MASTER BINARY DATA RG1PM.MAS
CALIBRATION BINARY DATA FILERG1PM.CAL
CLASSICAL ITEM STATISTICS RG1PM.IST
RG1PM.PAR
RG1PM.SCO
ESTIMATED COVARIANCE FILE RG1PM.COV
RG1PM.TST
==========================
MAIN TEST LENGTHS:
25
>INPUT NTOtal = 25,
NALt = 3,
NIDchar = 11;
204
=========================
1
25
3
11
NUMBER OF GROUPS
1
1
TYPE OF DATA
>ITEMS ;
TEST SPECIFICATIONS
===================
INUmber = (1(1)25);
NUMBER OF ITEMS: 25
ITEM ITEM
ITEM ITEM
ITEM ITEM
ITEM ITEM
205
NUMBER NAME
NUMBER
NAME
----------------------------------------------------------------------1 ITEM0001
9 ITEM0009
17 ITEM0017 25 ITEM0025
2 ITEM0002 10 ITEM0010 18 ITEM0018
3 ITEM0003 11 ITEM0011 19 ITEM0019
4 ITEM0004 12 ITEM0012 20 ITEM0020
5 ITEM0005 13 ITEM0013 21 ITEM0021
6 ITEM0006 14 ITEM0014 22 ITEM0022
7 ITEM0007 15 ITEM0015 23 ITEM0023
8 ITEM0008 16 ITEM0016 24 ITEM0024
-----------------------------------------------------------------------
FORM SPECIFICATIONS
===================
(11A1, 25A1)
OBSERVATION #
1 WEIGHT:
GROUP #: 1
TRIED RIGHT
25.000 7.000
206
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 0.0 0.0 1.0 1.0 0.0 1.0 1.0 1.0 0.0 0.0
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0
ITEM 21 22 23 24 25
TRIED 1.0 1.0 1.0 1.0 1.0
RIGHT 0.0 0.0 0.0 0.0 0.0
OBSERVATION #
2 WEIGHT:
GROUP #: 1
TRIED RIGHT
25.000 11.000
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 0.0 1.0 1.0 0.0 1.0 1.0 0.0 1.0
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
ITEM
21 22 23 24 25
207
TRIED 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 0.0 0.0 1.0
999 OBSERVATIONS READ FROM FILE: C:\25BY1000\RG.DAT
999 OBSERVATIONS WRITTEN TO FILE: RG1PM.MAS
ITEM NAME
#TRIED #RIGHT PCT
------------------------------------------------------------------------1 ITEM0001 999.0 694.0 69.5 -0.82 0.246 0.324
2 ITEM0002 999.0 477.0 47.7 0.09 0.155 0.194
3 ITEM0003 999.0 579.0 58.0 -0.32 0.237 0.300
4 ITEM0004 999.0 571.0 57.2 -0.29 0.218 0.275
5 ITEM0005 999.0 461.0 46.1 0.15 0.159 0.199
6 ITEM0006 999.0 801.0 80.2 -1.40 0.266 0.380
7 ITEM0007 999.0 516.0 51.7 -0.07 0.236 0.295
8 ITEM0008 999.0 703.0 70.4 -0.86 0.219 0.289
9 ITEM0009 999.0 390.0 39.0 0.45 0.225 0.286
10 ITEM0010 999.0 560.0 56.1 -0.24 0.268 0.338
11 ITEM0011 999.0 264.0 26.4 1.02 0.022 0.030
12 ITEM0012 999.0 511.0 51.2 -0.05 0.256 0.321
13 ITEM0013 999.0 500.0 50.1 0.00 0.092 0.115
14 ITEM0014 999.0 743.0 74.4 -1.07 0.200 0.271
15 ITEM0015 999.0 195.0 19.5 1.42 0.091 0.130
16 ITEM0016 999.0 210.0 21.0 1.32 0.071 0.100
17 ITEM0017 999.0 281.0 28.1 0.94 0.047 0.062
18 ITEM0018 999.0 401.0 40.1 0.40 0.101 0.129
19 ITEM0019 999.0 284.0 28.4 0.92 0.128 0.170
20 ITEM0020 999.0 271.0 27.1 0.99 0.031 0.042
21 ITEM0021 999.0 290.0 29.0 0.89 0.108 0.144
22 ITEM0022 999.0 374.0 37.4 0.51 0.173 0.221
23 ITEM0023 999.0 198.0 19.8 1.40 0.043 0.061
24 ITEM0024 999.0 251.0 25.1 1.09 0.068 0.093
25 ITEM0025 999.0 187.0 18.7 1.47 0.069 0.100
------------------------------------------------------------------------208
IN PHASE-1
IN PHASE-1
11/29/2011 15:08:45
PH2
1
BILOG-MG V3.0
REV 19990329.1300
MODEL
*** PHASE 2 ***
25 by 1000
TPRior,
209
FLOat;
======================
20
0.0100
1.0000
2
NO
DATA HANDLING:
NO
PROGRAM DEFAULTS
ITEM CONSTRAINTS IF PRESENT
WILL BE UPDATED EACH CYCLE
1
--------------------------------------------------------------------------------
******************************
TEST0001
******************************
METHOD OF SOLUTION:
210
1
2
3
4
5
POINT -0.4000E+01 -0.3429E+01 -0.2857E+01 -0.2286E+01 -0.1714E+01
WEIGHT 0.7648E-04 0.6387E-03 0.3848E-02 0.1673E-01 0.5245E-01
6
7
8
9
10
POINT -0.1143E+01 -0.5714E+00 -0.8882E-15 0.5714E+00 0.1143E+01
WEIGHT 0.1186E+00 0.1936E+00 0.2280E+00 0.1936E+00 0.1186E+00
11
12
13
14
15
POINT 0.1714E+01 0.2286E+01 0.2857E+01 0.3429E+01 0.4000E+01
WEIGHT 0.5245E-01 0.1673E-01 0.3848E-02 0.6387E-03 0.7648E-04
THRESHOLDS
SLOPES
ASYMPTOTES
ITEM
BETA
---------------------------------------------------------------------ITEM0001 0.000 2.000
ITEM0002 0.000 2.000
ITEM0003 0.000 2.000
ITEM0004 0.000 2.000
ITEM0005 0.000 2.000
ITEM0006 0.000 2.000
ITEM0007 0.000 2.000
ITEM0008 0.000 2.000
ITEM0009 0.000 2.000
ITEM0010 0.000 2.000
ITEM0011 0.000 2.000
ITEM0012 0.000 2.000
211
ITEM0013 0.000 2.000
ITEM0014 0.000 2.000
ITEM0015 0.000 2.000
ITEM0016 0.000 2.000
ITEM0017 0.000 2.000
ITEM0018 0.000 2.000
ITEM0019 0.000 2.000
ITEM0020 0.000 2.000
ITEM0021 0.000 2.000
ITEM0022 0.000 2.000
ITEM0023 0.000 2.000
ITEM0024 0.000 2.000
ITEM0025 0.000 2.000
----------------------------------------------------------------------
[E-M CYCLES]
-2 LOG LIKELIHOOD =
CYCLE
30330.381
-2 LOG LIKELIHOOD =
30268.635
UPDATED PRIOR ON THRESHOLDS; MEAN & SD =
CYCLE
0.86349
2.00000
-2 LOG LIKELIHOOD =
30246.118
212
CYCLE
0.73469
2.00000
0.69411
2.00000
0.69971
2.00000
30239.836
-2 LOG LIKELIHOOD =
30237.320
CYCLE
2.00000
-2 LOG LIKELIHOOD =
CYCLE
0.77382
[NEWTON CYCLES]
-2 LOG LIKELIHOOD:
CYCLE
30237.2725
213
---------------------------------------------------------------------------18. 41. 39. 155. 220. 221. 191. 75. 39.
----------------------------------------------------------------------------2.628 -1.890 -1.453 -0.935 -0.331 0.258 0.806 1.415 2.098
---------------------------------------------------------------------------1
ITEM
CHISQ
DF
S.E.
S.E.
S.E.
S.E.
S.E. (PROB)
------------------------------------------------------------------------------ITEM0001 | 0.858 | 0.469 | -1.828 | 0.425 | 0.000 | 34.8 7.0
| 0.072* | 0.020* | 0.153* | 0.018* | 0.000* | (0.0000)
|
|
|
|
|
|
ITEM0002 | -0.096 | 0.469 | 0.206 | 0.425 | 0.000 | 15.0 8.0
| 0.066* | 0.020* | 0.140* | 0.018* | 0.000* | (0.0583)
|
|
|
|
|
|
ITEM0003 | 0.335 | 0.469 | -0.713 | 0.425 | 0.000 | 35.8 9.0
| 0.067* | 0.020* | 0.143* | 0.018* | 0.000* | (0.0000)
|
|
|
|
|
|
ITEM0004 | 0.300 | 0.469 | -0.640 | 0.425 | 0.000 | 32.7 9.0
| 0.067* | 0.020* | 0.143* | 0.018* | 0.000* | (0.0001)
|
|
|
|
|
|
ITEM0005 | -0.164 | 0.469 | 0.349 | 0.425 | 0.000 | 13.2 9.0
| 0.066* | 0.020* | 0.140* | 0.018* | 0.000* | (0.1554)
|
|
|
|
|
|
ITEM0006 | 1.451 | 0.469 | -3.092 | 0.425 | 0.000 | 55.0 9.0
| 0.083* | 0.020* | 0.177* | 0.018* | 0.000* | (0.0000)
|
|
|
|
|
|
ITEM0007 | 0.067 | 0.469 | -0.144 | 0.425 | 0.000 | 32.5 8.0
| 0.066* | 0.020* | 0.142* | 0.018* | 0.000* | (0.0001)
|
|
|
|
|
|
ITEM0008 | 0.902 | 0.469 | -1.923 | 0.425 | 0.000 | 42.6 8.0
214
| 0.072* | 0.020* | 0.154* | 0.018* | 0.000* | (0.0000)
|
|
|
|
|
|
ITEM0009 | -0.469 | 0.469 | 0.999 | 0.425 | 0.000 | 27.7
| 0.068* | 0.020* | 0.145* | 0.018* | 0.000* | (0.0005)
|
|
|
|
|
|
ITEM0010 | 0.253 | 0.469 | -0.540 | 0.425 | 0.000 | 48.8
| 0.067* | 0.020* | 0.143* | 0.018* | 0.000* | (0.0000)
|
|
|
|
|
|
ITEM0011 | -1.071 | 0.469 | 2.282 | 0.425 | 0.000 | 6.5
| 0.072* | 0.020* | 0.154* | 0.018* | 0.000* | (0.5861)
|
|
|
|
|
|
ITEM0012 | 0.046 | 0.469 | -0.099 | 0.425 | 0.000 | 43.7
| 0.067* | 0.020* | 0.142* | 0.018* | 0.000* | (0.0000)
|
|
|
|
|
|
ITEM0013 | 0.000 | 0.469 | -0.001 | 0.425 | 0.000 | 5.4
| 0.065* | 0.020* | 0.138* | 0.018* | 0.000* | (0.8002)
|
|
|
|
|
|
ITEM0014 | 1.110 | 0.469 | -2.365 | 0.425 | 0.000 | 25.4
| 0.075* | 0.020* | 0.160* | 0.018* | 0.000* | (0.0013)
|
|
|
|
|
|
ITEM0015 | -1.475 | 0.469 | 3.143 | 0.425 | 0.000 | 5.2
| 0.081* | 0.020* | 0.173* | 0.018* | 0.000* | (0.7338)
|
|
|
|
|
|
ITEM0016 | -1.380 | 0.469 | 2.940 | 0.425 | 0.000 | 6.7
| 0.079* | 0.020* | 0.168* | 0.018* | 0.000* | (0.5747)
|
|
|
|
|
|
ITEM0017 | -0.982 | 0.469 | 2.093 | 0.425 | 0.000 | 3.6
| 0.071* | 0.020* | 0.152* | 0.018* | 0.000* | (0.8928)
|
|
|
|
|
|
ITEM0018 | -0.421 | 0.469 | 0.897 | 0.425 | 0.000 | 8.8
| 0.066* | 0.020* | 0.141* | 0.018* | 0.000* | (0.3562)
|
|
|
|
|
|
ITEM0019 | -0.967 | 0.469 | 2.060 | 0.425 | 0.000 | 15.0
| 0.072* | 0.020* | 0.154* | 0.018* | 0.000* | (0.0588)
|
|
|
|
|
|
ITEM0020 | -1.034 | 0.469 | 2.203 | 0.425 | 0.000 | 14.7
| 0.072* | 0.020* | 0.153* | 0.018* | 0.000* | (0.0647)
|
|
|
|
|
|
ITEM0021 | -0.936 | 0.469 | 1.995 | 0.425 | 0.000 | 9.6
| 0.071* | 0.020* | 0.152* | 0.018* | 0.000* | (0.2929)
8.0
9.0
8.0
8.0
9.0
8.0
8.0
8.0
8.0
8.0
8.0
8.0
8.0
215
|
|
|
|
|
|
ITEM0022 | -0.540 | 0.469 | 1.150 | 0.425 | 0.000 | 12.5
| 0.068* | 0.020* | 0.145* | 0.018* | 0.000* | (0.1303)
|
|
|
|
|
|
ITEM0023 | -1.455 | 0.469 | 3.102 | 0.425 | 0.000 | 14.8
| 0.080* | 0.020* | 0.171* | 0.018* | 0.000* | (0.0629)
|
|
|
|
|
|
ITEM0024 | -1.141 | 0.469 | 2.432 | 0.425 | 0.000 | 10.3
| 0.074* | 0.020* | 0.158* | 0.018* | 0.000* | (0.2470)
|
|
|
|
|
|
ITEM0025 | -1.528 | 0.469 | 3.256 | 0.425 | 0.000 | 4.1
| 0.082* | 0.020* | 0.175* | 0.018* | 0.000* | (0.8451)
------------------------------------------------------------------------------* STANDARD ERROR
8.0
8.0
8.0
8.0
LARGEST CHANGE =
0.001358
524.4 205.0
(0.0000)
-------------------------------------------------------------------------------
PARAMETER
MEAN STN DEV
----------------------------------THRESHOLD 0.711 1.842
1
2
3
4
5
POINT
-0.4056E+01 -0.3477E+01 -0.2897E+01 -0.2318E+01 -0.1738E+01
POSTERIOR 0.1229E-03 0.9073E-03 0.4701E-02 0.1787E-01 0.5182E-01
6
7
8
9
10
POINT
-0.1159E+01 -0.5791E+00 0.3812E-03 0.5799E+00 0.1159E+01
POSTERIOR 0.1149E+00 0.1904E+00 0.2299E+00 0.1983E+00 0.1201E+00
POINT
11
12
13
14
15
0.1739E+01 0.2318E+01 0.2898E+01 0.3477E+01 0.4057E+01
216
POSTERIOR 0.5118E-01 0.1565E-01 0.3513E-02 0.5879E-03 0.7299E-04
MEAN
S.D.
0.00000
1.00000
IN PHASE-2
IN PHASE-2
11/29/2011 15:08:45
PH3
1
BILOG-MG V3.0
MODEL
*** PHASE 3 ***
25 by 1000
>SCORE METhod = 1;
INFORMATION
217
MAXIMUM LIKELIHOOD
RG1PM.SCO
RG1PM.PH3
TYPE OF RESCALING:
----------------------1
NONE REQUESTED
NONE REQUESTED
NONE REQUESTED
******************************
SCORING
******************************
1
WEIGHT TEST TRIED RIGHT PERCENT ABILITY
---------------------------------------------------------------1 Examinee001
|
|
1.00 TEST0001 25
7 28.00 | -1.6043 1.0190 |
1 Examinee002
|
|
1.00 TEST0001 25 11 44.00 | 0.1408 0.9291 |
1 Examinee003
|
|
1.00 TEST0001 25 11 44.00 | 0.1408 0.9291 |
1 Examinee004
|
|
1.00 TEST0001 25 12 48.00 | 0.5426 0.9226 |
1 Examinee005
|
|
1.00 TEST0001 25 10 40.00 | -0.2690 0.9410 |
1 Examinee006
|
|
1.00 TEST0001 25
9 36.00 | -0.6919 0.9590 |
1 Examinee007
|
|
1.00 TEST0001 25 10 40.00 | -0.2690 0.9410 |
S.E.
218
1 Examinee008
1.00 TEST0001
1 Examinee009
1.00 TEST0001
1 Examinee010
1.00 TEST0001
1 Examinee011
1.00 TEST0001
1 Examinee012
1.00 TEST0001
1 Examinee013
1.00 TEST0001
1 Examinee014
1.00 TEST0001
1 Examinee015
1.00 TEST0001
1 Examinee016
1.00 TEST0001
1 Examinee017
1.00 TEST0001
1 Examinee018
1.00 TEST0001
1 Examinee019
1.00 TEST0001
1 Examinee020
1.00 TEST0001
1 Examinee021
1.00 TEST0001
1 Examinee022
1.00 TEST0001
1 Examinee023
1.00 TEST0001
1 Examinee024
1.00 TEST0001
1 Examinee025
1.00 TEST0001
1 Examinee026
1.00 TEST0001
1 Examinee027
1.00 TEST0001
25
11
25
14
25
9
25
12
25
13
25
16
25
15
25
10
25
13
25
16
25
8
25
5
25
12
25
11
25
11
25
14
25
13
25
7
25
10
25
15
|
44.00 |
|
56.00 |
|
36.00 |
|
48.00 |
|
52.00 |
|
64.00 |
|
60.00 |
|
40.00 |
|
52.00 |
|
64.00 |
|
32.00 |
|
20.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
56.00 |
|
52.00 |
|
28.00 |
|
40.00 |
|
60.00 |
|
0.1408
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1.3406
|
-0.6919
|
0.5426
|
0.9411
|
2.1619
|
1.7458
|
-0.2690
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0.9411
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2.1619
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-1.1343
|
-2.6776
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0.5426
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0.1408
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0.1408
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1.3406
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0.9411
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-1.6043
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-0.2690
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1.7458
0.9291 |
0.9252 |
0.9590 |
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0.9213 |
0.9500 |
0.9345 |
0.9410 |
0.9213 |
0.9500 |
0.9844 |
1.1311 |
0.9226 |
0.9291 |
0.9291 |
0.9252 |
0.9213 |
1.0190 |
0.9410 |
0.9345 |
219
1 Examinee028
1.00 TEST0001
1 Examinee029
1.00 TEST0001
1 Examinee030
1.00 TEST0001
1 Examinee031
1.00 TEST0001
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1.00 TEST0001
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25
10
25
13
25
16
25
16
25
13
25
11
25
18
25
12
25
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25
10
25
14
25
10
25
14
25
13
25
7
25
13
25
11
25
11
25
13
25
8
|
40.00 |
|
52.00 |
|
64.00 |
|
64.00 |
|
52.00 |
|
44.00 |
|
72.00 |
|
48.00 |
|
32.00 |
|
40.00 |
|
56.00 |
|
40.00 |
|
56.00 |
|
52.00 |
|
28.00 |
|
52.00 |
|
44.00 |
|
44.00 |
|
52.00 |
|
32.00 |
|
-0.2690
|
0.9411
|
2.1619
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|
0.9411
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0.1408
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3.0533
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0.5426
|
-1.1343
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-0.2690
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1.3406
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-0.2690
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1.3406
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0.9411
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-1.6043
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0.9411
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0.1408
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0.1408
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0.9411
|
-1.1343
0.9410 |
0.9213 |
0.9500 |
0.9500 |
0.9213 |
0.9291 |
1.0052 |
0.9226 |
0.9844 |
0.9410 |
0.9252 |
0.9410 |
0.9252 |
0.9213 |
1.0190 |
0.9213 |
0.9291 |
0.9291 |
0.9213 |
0.9844 |
220
1 Examinee048
1.00 TEST0001
1 Examinee049
1.00 TEST0001
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1.00 TEST0001
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25
11
25
13
25
13
25
9
25
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25
11
25
9
25
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25
13
25
16
25
16
25
8
25
10
25
11
25
8
25
13
25
12
25
11
25
13
25
13
|
44.00 |
|
52.00 |
|
52.00 |
|
36.00 |
|
52.00 |
|
44.00 |
|
36.00 |
|
32.00 |
|
52.00 |
|
64.00 |
|
64.00 |
|
32.00 |
|
40.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
48.00 |
|
44.00 |
|
52.00 |
|
52.00 |
|
0.1408
|
0.9411
|
0.9411
|
-0.6919
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0.1408
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-0.6919
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-1.1343
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0.9411
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2.1619
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|
-1.1343
|
-0.2690
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0.1408
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-1.1343
|
0.9411
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0.5426
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0.1408
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0.9411
|
0.9411
0.9291 |
0.9213 |
0.9213 |
0.9590 |
0.9213 |
0.9291 |
0.9590 |
0.9844 |
0.9213 |
0.9500 |
0.9500 |
0.9844 |
0.9410 |
0.9291 |
0.9844 |
0.9213 |
0.9226 |
0.9291 |
0.9213 |
0.9213 |
221
1 Examinee068
1.00 TEST0001
1 Examinee069
1.00 TEST0001
1 Examinee070
1.00 TEST0001
1 Examinee071
1.00 TEST0001
1 Examinee072
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25
13
25
9
25
15
25
11
25
16
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25
13
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25
18
25
15
25
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25
14
25
17
25
16
25
8
25
11
25
10
25
11
25
14
25
13
|
52.00 |
|
36.00 |
|
60.00 |
|
44.00 |
|
64.00 |
|
52.00 |
|
52.00 |
|
64.00 |
|
72.00 |
|
60.00 |
|
28.00 |
|
56.00 |
|
68.00 |
|
64.00 |
|
32.00 |
|
44.00 |
|
40.00 |
|
44.00 |
|
56.00 |
|
52.00 |
|
0.9411
|
-0.6919
|
1.7458
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0.1408
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0.9411
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0.9411
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2.1619
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3.0533
|
1.7458
|
-1.6043
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1.3406
|
2.5950
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2.1619
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-1.1343
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0.1408
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-0.2690
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0.1408
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1.3406
|
0.9411
0.9213 |
0.9590 |
0.9345 |
0.9291 |
0.9500 |
0.9213 |
0.9213 |
0.9500 |
1.0052 |
0.9345 |
1.0190 |
0.9252 |
0.9729 |
0.9500 |
0.9844 |
0.9291 |
0.9410 |
0.9291 |
0.9252 |
0.9213 |
222
1 Examinee088
1.00 TEST0001
1 Examinee089
1.00 TEST0001
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1.00 TEST0001
1 Examinee091
1.00 TEST0001
1 Examinee092
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25
11
25
10
25
13
25
12
25
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25
8
25
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25
11
25
17
25
12
25
18
25
11
25
9
25
10
25
11
25
15
25
11
25
14
25
11
|
44.00 |
|
40.00 |
|
52.00 |
|
48.00 |
|
40.00 |
|
52.00 |
|
32.00 |
|
52.00 |
|
44.00 |
|
68.00 |
|
48.00 |
|
72.00 |
|
44.00 |
|
36.00 |
|
40.00 |
|
44.00 |
|
60.00 |
|
44.00 |
|
56.00 |
|
44.00 |
|
0.1408
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-0.2690
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0.9411
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0.5426
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-0.2690
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0.9411
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-1.1343
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0.1408
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2.5950
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0.5426
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3.0533
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0.1408
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-0.6919
|
-0.2690
|
0.1408
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1.7458
|
0.1408
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1.3406
|
0.1408
0.9291 |
0.9410 |
0.9213 |
0.9226 |
0.9410 |
0.9213 |
0.9844 |
0.9213 |
0.9291 |
0.9729 |
0.9226 |
1.0052 |
0.9291 |
0.9590 |
0.9410 |
0.9291 |
0.9345 |
0.9291 |
0.9252 |
0.9291 |
223
1 Examinee108
1.00 TEST0001
1 Examinee109
1.00 TEST0001
1 Examinee110
1.00 TEST0001
1 Examinee111
1.00 TEST0001
1 Examinee112
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25
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25
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25
10
25
12
25
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25
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25
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25
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25
15
25
10
25
9
25
8
25
7
25
8
25
11
25
11
25
12
25
14
|
32.00 |
|
28.00 |
|
40.00 |
|
48.00 |
|
48.00 |
|
40.00 |
|
28.00 |
|
36.00 |
|
52.00 |
|
36.00 |
|
60.00 |
|
40.00 |
|
36.00 |
|
32.00 |
|
28.00 |
|
32.00 |
|
44.00 |
|
44.00 |
|
48.00 |
|
56.00 |
|
-1.1343
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-0.6919
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0.9411
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-0.6919
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1.7458
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-0.2690
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-0.6919
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-1.1343
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-1.6043
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-1.1343
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0.1408
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0.1408
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0.5426
|
1.3406
0.9844 |
1.0190 |
0.9410 |
0.9226 |
0.9226 |
0.9410 |
1.0190 |
0.9590 |
0.9213 |
0.9590 |
0.9345 |
0.9410 |
0.9590 |
0.9844 |
1.0190 |
0.9844 |
0.9291 |
0.9291 |
0.9226 |
0.9252 |
224
1 Examinee128
1.00 TEST0001
1 Examinee129
1.00 TEST0001
1 Examinee130
1.00 TEST0001
1 Examinee131
1.00 TEST0001
1 Examinee132
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1.00 TEST0001
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25
11
25
6
25
5
25
9
25
14
25
12
25
4
25
9
25
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25
14
25
7
25
8
25
17
25
8
25
7
25
10
25
12
25
8
25
10
|
44.00 |
|
24.00 |
|
20.00 |
|
36.00 |
|
56.00 |
|
48.00 |
|
16.00 |
|
36.00 |
|
40.00 |
|
40.00 |
|
56.00 |
|
28.00 |
|
32.00 |
|
68.00 |
|
32.00 |
|
28.00 |
|
40.00 |
|
48.00 |
|
32.00 |
|
40.00 |
|
0.1408
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-2.1131
|
-2.6776
|
-0.6919
|
1.3406
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0.5426
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-3.3255
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-0.6919
|
-0.2690
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-0.2690
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1.3406
|
-1.6043
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-1.1343
|
2.5950
|
-1.1343
|
-1.6043
|
-0.2690
|
0.5426
|
-1.1343
|
-0.2690
0.9291 |
1.0661 |
1.1311 |
0.9590 |
0.9252 |
0.9226 |
1.2245 |
0.9590 |
0.9410 |
0.9410 |
0.9252 |
1.0190 |
0.9844 |
0.9729 |
0.9844 |
1.0190 |
0.9410 |
0.9226 |
0.9844 |
0.9410 |
225
1 Examinee148
1.00 TEST0001
1 Examinee149
1.00 TEST0001
1 Examinee150
1.00 TEST0001
1 Examinee151
1.00 TEST0001
1 Examinee152
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25
8
25
7
25
12
25
12
25
11
25
16
25
16
25
10
25
10
25
16
25
15
25
19
25
16
25
17
25
5
25
10
25
17
25
7
25
12
25
8
|
32.00 |
|
28.00 |
|
48.00 |
|
48.00 |
|
44.00 |
|
64.00 |
|
64.00 |
|
40.00 |
|
40.00 |
|
64.00 |
|
60.00 |
|
76.00 |
|
64.00 |
|
68.00 |
|
20.00 |
|
40.00 |
|
68.00 |
|
28.00 |
|
48.00 |
|
32.00 |
|
-1.1343
|
-1.6043
|
0.5426
|
0.5426
|
0.1408
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2.1619
|
2.1619
|
-0.2690
|
-0.2690
|
2.1619
|
1.7458
|
3.5477
|
2.1619
|
2.5950
|
-2.6776
|
-0.2690
|
2.5950
|
-1.6043
|
0.5426
|
-1.1343
0.9844 |
1.0190 |
0.9226 |
0.9226 |
0.9291 |
0.9500 |
0.9500 |
0.9410 |
0.9410 |
0.9500 |
0.9345 |
1.0503 |
0.9500 |
0.9729 |
1.1311 |
0.9410 |
0.9729 |
1.0190 |
0.9226 |
0.9844 |
226
1 Examinee168
1.00 TEST0001
1 Examinee169
1.00 TEST0001
1 Examinee170
1.00 TEST0001
1 Examinee171
1.00 TEST0001
1 Examinee172
1.00 TEST0001
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1.00 TEST0001
1 Examinee174
1.00 TEST0001
1 Examinee175
1.00 TEST0001
1 Examinee176
1.00 TEST0001
1 Examinee177
1.00 TEST0001
1 Examinee178
1.00 TEST0001
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1 Examinee180
1.00 TEST0001
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1 Examinee182
1.00 TEST0001
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1.00 TEST0001
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25
13
25
16
25
9
25
7
25
14
25
10
25
17
25
17
25
14
25
8
25
12
25
9
25
11
25
13
25
13
25
9
25
12
25
9
25
11
25
10
|
52.00 |
|
64.00 |
|
36.00 |
|
28.00 |
|
56.00 |
|
40.00 |
|
68.00 |
|
68.00 |
|
56.00 |
|
32.00 |
|
48.00 |
|
36.00 |
|
44.00 |
|
52.00 |
|
52.00 |
|
36.00 |
|
48.00 |
|
36.00 |
|
44.00 |
|
40.00 |
|
0.9411
|
2.1619
|
-0.6919
|
-1.6043
|
1.3406
|
-0.2690
|
2.5950
|
2.5950
|
1.3406
|
-1.1343
|
0.5426
|
-0.6919
|
0.1408
|
0.9411
|
0.9411
|
-0.6919
|
0.5426
|
-0.6919
|
0.1408
|
-0.2690
0.9213 |
0.9500 |
0.9590 |
1.0190 |
0.9252 |
0.9410 |
0.9729 |
0.9729 |
0.9252 |
0.9844 |
0.9226 |
0.9590 |
0.9291 |
0.9213 |
0.9213 |
0.9590 |
0.9226 |
0.9590 |
0.9291 |
0.9410 |
227
1 Examinee188
1.00 TEST0001
1 Examinee189
1.00 TEST0001
1 Examinee190
1.00 TEST0001
1 Examinee191
1.00 TEST0001
1 Examinee192
1.00 TEST0001
1 Examinee193
1.00 TEST0001
1 Examinee194
1.00 TEST0001
1 Examinee195
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1 Examinee197
1.00 TEST0001
1 Examinee198
1.00 TEST0001
1 Examinee199
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1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
1 Examinee203
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1.00 TEST0001
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1.00 TEST0001
1 Examinee207
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25
12
25
12
25
8
25
11
25
8
25
12
25
12
25
15
25
20
25
13
25
15
25
10
25
11
25
12
25
14
25
16
25
12
25
11
25
11
25
9
|
48.00 |
|
48.00 |
|
32.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
48.00 |
|
60.00 |
|
80.00 |
|
52.00 |
|
60.00 |
|
40.00 |
|
44.00 |
|
48.00 |
|
56.00 |
|
64.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
36.00 |
|
0.5426
|
0.5426
|
-1.1343
|
0.1408
|
-1.1343
|
0.5426
|
0.5426
|
1.7458
|
4.0000
|
0.9411
|
1.7458
|
-0.2690
|
0.1408
|
0.5426
|
1.3406
|
2.1619
|
0.5426
|
0.1408
|
0.1408
|
-0.6919
0.9226 |
0.9226 |
0.9844 |
0.9291 |
0.9844 |
0.9226 |
0.9226 |
0.9345 |
999.0000 |
0.9213 |
0.9345 |
0.9410 |
0.9291 |
0.9226 |
0.9252 |
0.9500 |
0.9226 |
0.9291 |
0.9291 |
0.9590 |
228
1 Examinee208
1.00 TEST0001
1 Examinee209
1.00 TEST0001
1 Examinee210
1.00 TEST0001
1 Examinee211
1.00 TEST0001
1 Examinee212
1.00 TEST0001
1 Examinee213
1.00 TEST0001
1 Examinee214
1.00 TEST0001
1 Examinee215
1.00 TEST0001
1 Examinee216
1.00 TEST0001
1 Examinee217
1.00 TEST0001
1 Examinee218
1.00 TEST0001
1 Examinee219
1.00 TEST0001
1 Examinee220
1.00 TEST0001
1 Examinee221
1.00 TEST0001
1 Examinee222
1.00 TEST0001
1 Examinee223
1.00 TEST0001
1 Examinee224
1.00 TEST0001
1 Examinee225
1.00 TEST0001
1 Examinee226
1.00 TEST0001
1 Examinee227
1.00 TEST0001
25
11
25
12
25
12
25
10
25
7
25
7
25
8
25
15
25
12
25
17
25
15
25
17
25
8
25
22
25
14
25
12
25
16
25
16
25
19
25
20
|
44.00 |
|
48.00 |
|
48.00 |
|
40.00 |
|
28.00 |
|
28.00 |
|
32.00 |
|
60.00 |
|
48.00 |
|
68.00 |
|
60.00 |
|
68.00 |
|
32.00 |
|
88.00 |
|
56.00 |
|
48.00 |
|
64.00 |
|
64.00 |
|
76.00 |
|
80.00 |
|
0.1408
|
0.5426
|
0.5426
|
-0.2690
|
-1.6043
|
-1.6043
|
-1.1343
|
1.7458
|
0.5426
|
2.5950
|
1.7458
|
2.5950
|
-1.1343
|
4.0000
|
1.3406
|
0.5426
|
2.1619
|
2.1619
|
3.5477
|
4.0000
0.9291 |
0.9226 |
0.9226 |
0.9410 |
1.0190 |
1.0190 |
0.9844 |
0.9345 |
0.9226 |
0.9729 |
0.9345 |
0.9729 |
0.9844 |
999.0000 |
0.9252 |
0.9226 |
0.9500 |
0.9500 |
1.0503 |
999.0000 |
229
1 Examinee228
1.00 TEST0001
1 Examinee229
1.00 TEST0001
1 Examinee230
1.00 TEST0001
1 Examinee231
1.00 TEST0001
1 Examinee232
1.00 TEST0001
1 Examinee233
1.00 TEST0001
1 Examinee234
1.00 TEST0001
1 Examinee235
1.00 TEST0001
1 Examinee236
1.00 TEST0001
1 Examinee237
1.00 TEST0001
1 Examinee238
1.00 TEST0001
1 Examinee239
1.00 TEST0001
1 Examinee240
1.00 TEST0001
1 Examinee241
1.00 TEST0001
1 Examinee242
1.00 TEST0001
1 Examinee243
1.00 TEST0001
1 Examinee244
1.00 TEST0001
1 Examinee245
1.00 TEST0001
1 Examinee246
1.00 TEST0001
1 Examinee247
1.00 TEST0001
25
11
25
9
25
13
25
10
25
8
25
9
25
16
25
9
25
12
25
11
25
11
25
16
25
10
25
13
25
14
25
9
25
10
25
8
25
12
25
7
|
44.00 |
|
36.00 |
|
52.00 |
|
40.00 |
|
32.00 |
|
36.00 |
|
64.00 |
|
36.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
64.00 |
|
40.00 |
|
52.00 |
|
56.00 |
|
36.00 |
|
40.00 |
|
32.00 |
|
48.00 |
|
28.00 |
|
0.1408
|
-0.6919
|
0.9411
|
-0.2690
|
-1.1343
|
-0.6919
|
2.1619
|
-0.6919
|
0.5426
|
0.1408
|
0.1408
|
2.1619
|
-0.2690
|
0.9411
|
1.3406
|
-0.6919
|
-0.2690
|
-1.1343
|
0.5426
|
-1.6043
0.9291 |
0.9590 |
0.9213 |
0.9410 |
0.9844 |
0.9590 |
0.9500 |
0.9590 |
0.9226 |
0.9291 |
0.9291 |
0.9500 |
0.9410 |
0.9213 |
0.9252 |
0.9590 |
0.9410 |
0.9844 |
0.9226 |
1.0190 |
230
1 Examinee248
1.00 TEST0001
1 Examinee249
1.00 TEST0001
1 Examinee250
1.00 TEST0001
1 Examinee251
1.00 TEST0001
1 Examinee252
1.00 TEST0001
1 Examinee253
1.00 TEST0001
1 Examinee254
1.00 TEST0001
1 Examinee255
1.00 TEST0001
1 Examinee256
1.00 TEST0001
1 Examinee257
1.00 TEST0001
1 Examinee258
1.00 TEST0001
1 Examinee259
1.00 TEST0001
1 Examinee260
1.00 TEST0001
1 Examinee261
1.00 TEST0001
1 Examinee262
1.00 TEST0001
1 Examinee263
1.00 TEST0001
1 Examinee264
1.00 TEST0001
1 Examinee265
1.00 TEST0001
1 Examinee266
1.00 TEST0001
1 Examinee267
1.00 TEST0001
25
12
25
8
25
8
25
10
25
12
25
5
25
12
25
9
25
17
25
9
25
16
25
14
25
12
25
15
25
12
25
9
25
9
25
6
25
7
25
5
|
48.00 |
|
32.00 |
|
32.00 |
|
40.00 |
|
48.00 |
|
20.00 |
|
48.00 |
|
36.00 |
|
68.00 |
|
36.00 |
|
64.00 |
|
56.00 |
|
48.00 |
|
60.00 |
|
48.00 |
|
36.00 |
|
36.00 |
|
24.00 |
|
28.00 |
|
20.00 |
|
0.5426
|
-1.1343
|
-1.1343
|
-0.2690
|
0.5426
|
-2.6776
|
0.5426
|
-0.6919
|
2.5950
|
-0.6919
|
2.1619
|
1.3406
|
0.5426
|
1.7458
|
0.5426
|
-0.6919
|
-0.6919
|
-2.1131
|
-1.6043
|
-2.6776
0.9226 |
0.9844 |
0.9844 |
0.9410 |
0.9226 |
1.1311 |
0.9226 |
0.9590 |
0.9729 |
0.9590 |
0.9500 |
0.9252 |
0.9226 |
0.9345 |
0.9226 |
0.9590 |
0.9590 |
1.0661 |
1.0190 |
1.1311 |
231
1 Examinee268
1.00 TEST0001
1 Examinee269
1.00 TEST0001
1 Examinee270
1.00 TEST0001
1 Examinee271
1.00 TEST0001
1 Examinee272
1.00 TEST0001
1 Examinee273
1.00 TEST0001
1 Examinee274
1.00 TEST0001
1 Examinee275
1.00 TEST0001
1 Examinee276
1.00 TEST0001
1 Examinee277
1.00 TEST0001
1 Examinee278
1.00 TEST0001
1 Examinee279
1.00 TEST0001
1 Examinee280
1.00 TEST0001
1 Examinee281
1.00 TEST0001
1 Examinee282
1.00 TEST0001
1 Examinee283
1.00 TEST0001
1 Examinee284
1.00 TEST0001
1 Examinee285
1.00 TEST0001
1 Examinee286
1.00 TEST0001
1 Examinee287
1.00 TEST0001
25
14
25
6
25
11
25
8
25
7
25
9
25
14
25
13
25
13
25
12
25
10
25
11
25
13
25
9
25
13
25
13
25
10
25
10
25
9
25
14
|
56.00 |
|
24.00 |
|
44.00 |
|
32.00 |
|
28.00 |
|
36.00 |
|
56.00 |
|
52.00 |
|
52.00 |
|
48.00 |
|
40.00 |
|
44.00 |
|
52.00 |
|
36.00 |
|
52.00 |
|
52.00 |
|
40.00 |
|
40.00 |
|
36.00 |
|
56.00 |
|
1.3406
|
-2.1131
|
0.1408
|
-1.1343
|
-1.6043
|
-0.6919
|
1.3406
|
0.9411
|
0.9411
|
0.5426
|
-0.2690
|
0.1408
|
0.9411
|
-0.6919
|
0.9411
|
0.9411
|
-0.2690
|
-0.2690
|
-0.6919
|
1.3406
0.9252 |
1.0661 |
0.9291 |
0.9844 |
1.0190 |
0.9590 |
0.9252 |
0.9213 |
0.9213 |
0.9226 |
0.9410 |
0.9291 |
0.9213 |
0.9590 |
0.9213 |
0.9213 |
0.9410 |
0.9410 |
0.9590 |
0.9252 |
232
1 Examinee288
1.00 TEST0001
1 Examinee289
1.00 TEST0001
1 Examinee290
1.00 TEST0001
1 Examinee291
1.00 TEST0001
1 Examinee292
1.00 TEST0001
1 Examinee293
1.00 TEST0001
1 Examinee294
1.00 TEST0001
1 Examinee295
1.00 TEST0001
1 Examinee296
1.00 TEST0001
1 Examinee297
1.00 TEST0001
1 Examinee298
1.00 TEST0001
1 Examinee299
1.00 TEST0001
1 Examinee300
1.00 TEST0001
1 Examinee301
1.00 TEST0001
1 Examinee302
1.00 TEST0001
1 Examinee303
1.00 TEST0001
1 Examinee304
1.00 TEST0001
1 Examinee305
1.00 TEST0001
1 Examinee306
1.00 TEST0001
1 Examinee307
1.00 TEST0001
25
11
25
10
25
12
25
8
25
12
25
9
25
10
25
13
25
13
25
10
25
13
25
10
25
9
25
13
25
10
25
5
25
10
25
14
25
6
25
13
|
44.00 |
|
40.00 |
|
48.00 |
|
32.00 |
|
48.00 |
|
36.00 |
|
40.00 |
|
52.00 |
|
52.00 |
|
40.00 |
|
52.00 |
|
40.00 |
|
36.00 |
|
52.00 |
|
40.00 |
|
20.00 |
|
40.00 |
|
56.00 |
|
24.00 |
|
52.00 |
|
0.1408
|
-0.2690
|
0.5426
|
-1.1343
|
0.5426
|
-0.6919
|
-0.2690
|
0.9411
|
0.9411
|
-0.2690
|
0.9411
|
-0.2690
|
-0.6919
|
0.9411
|
-0.2690
|
-2.6776
|
-0.2690
|
1.3406
|
-2.1131
|
0.9411
0.9291 |
0.9410 |
0.9226 |
0.9844 |
0.9226 |
0.9590 |
0.9410 |
0.9213 |
0.9213 |
0.9410 |
0.9213 |
0.9410 |
0.9590 |
0.9213 |
0.9410 |
1.1311 |
0.9410 |
0.9252 |
1.0661 |
0.9213 |
233
1 Examinee308
1.00 TEST0001
1 Examinee309
1.00 TEST0001
1 Examinee310
1.00 TEST0001
1 Examinee311
1.00 TEST0001
1 Examinee312
1.00 TEST0001
1 Examinee313
1.00 TEST0001
1 Examinee314
1.00 TEST0001
1 Examinee315
1.00 TEST0001
1 Examinee316
1.00 TEST0001
1 Examinee317
1.00 TEST0001
1 Examinee318
1.00 TEST0001
1 Examinee319
1.00 TEST0001
1 Examinee320
1.00 TEST0001
1 Examinee321
1.00 TEST0001
1 Examinee322
1.00 TEST0001
1 Examinee323
1.00 TEST0001
1 Examinee324
1.00 TEST0001
1 Examinee325
1.00 TEST0001
1 Examinee326
1.00 TEST0001
1 Examinee327
1.00 TEST0001
25
12
25
14
25
14
25
9
25
9
25
5
25
7
25
4
25
7
25
15
25
11
25
8
25
8
25
8
25
19
25
15
25
12
25
12
25
11
25
8
|
48.00 |
|
56.00 |
|
56.00 |
|
36.00 |
|
36.00 |
|
20.00 |
|
28.00 |
|
16.00 |
|
28.00 |
|
60.00 |
|
44.00 |
|
32.00 |
|
32.00 |
|
32.00 |
|
76.00 |
|
60.00 |
|
48.00 |
|
48.00 |
|
44.00 |
|
32.00 |
|
0.5426
|
1.3406
|
1.3406
|
-0.6919
|
-0.6919
|
-2.6776
|
-1.6043
|
-3.3255
|
-1.6043
|
1.7458
|
0.1408
|
-1.1343
|
-1.1343
|
-1.1343
|
3.5477
|
1.7458
|
0.5426
|
0.5426
|
0.1408
|
-1.1343
0.9226 |
0.9252 |
0.9252 |
0.9590 |
0.9590 |
1.1311 |
1.0190 |
1.2245 |
1.0190 |
0.9345 |
0.9291 |
0.9844 |
0.9844 |
0.9844 |
1.0503 |
0.9345 |
0.9226 |
0.9226 |
0.9291 |
0.9844 |
234
1 Examinee328
1.00 TEST0001
1 Examinee329
1.00 TEST0001
1 Examinee330
1.00 TEST0001
1 Examinee331
1.00 TEST0001
1 Examinee332
1.00 TEST0001
1 Examinee333
1.00 TEST0001
1 Examinee334
1.00 TEST0001
1 Examinee335
1.00 TEST0001
1 Examinee336
1.00 TEST0001
1 Examinee337
1.00 TEST0001
1 Examinee338
1.00 TEST0001
1 Examinee339
1.00 TEST0001
1 Examinee340
1.00 TEST0001
1 Examinee341
1.00 TEST0001
1 Examinee342
1.00 TEST0001
1 Examinee343
1.00 TEST0001
1 Examinee344
1.00 TEST0001
1 Examinee345
1.00 TEST0001
1 Examinee346
1.00 TEST0001
1 Examinee347
1.00 TEST0001
25
12
25
12
25
14
25
14
25
13
25
8
25
14
25
9
25
12
25
13
25
14
25
13
25
12
25
13
25
11
25
8
25
6
25
12
25
7
25
11
|
48.00 |
|
48.00 |
|
56.00 |
|
56.00 |
|
52.00 |
|
32.00 |
|
56.00 |
|
36.00 |
|
48.00 |
|
52.00 |
|
56.00 |
|
52.00 |
|
48.00 |
|
52.00 |
|
44.00 |
|
32.00 |
|
24.00 |
|
48.00 |
|
28.00 |
|
44.00 |
|
0.5426
|
0.5426
|
1.3406
|
1.3406
|
0.9411
|
-1.1343
|
1.3406
|
-0.6919
|
0.5426
|
0.9411
|
1.3406
|
0.9411
|
0.5426
|
0.9411
|
0.1408
|
-1.1343
|
-2.1131
|
0.5426
|
-1.6043
|
0.1408
0.9226 |
0.9226 |
0.9252 |
0.9252 |
0.9213 |
0.9844 |
0.9252 |
0.9590 |
0.9226 |
0.9213 |
0.9252 |
0.9213 |
0.9226 |
0.9213 |
0.9291 |
0.9844 |
1.0661 |
0.9226 |
1.0190 |
0.9291 |
235
1 Examinee348
1.00 TEST0001
1 Examinee349
1.00 TEST0001
1 Examinee350
1.00 TEST0001
1 Examinee351
1.00 TEST0001
1 Examinee352
1.00 TEST0001
1 Examinee353
1.00 TEST0001
1 Examinee354
1.00 TEST0001
1 Examinee355
1.00 TEST0001
1 Examinee356
1.00 TEST0001
1 Examinee357
1.00 TEST0001
1 Examinee358
1.00 TEST0001
1 Examinee359
1.00 TEST0001
1 Examinee360
1.00 TEST0001
1 Examinee361
1.00 TEST0001
1 Examinee362
1.00 TEST0001
1 Examinee363
1.00 TEST0001
1 Examinee364
1.00 TEST0001
1 Examinee365
1.00 TEST0001
1 Examinee366
1.00 TEST0001
1 Examinee367
1.00 TEST0001
25
14
25
11
25
6
25
9
25
14
25
10
25
10
25
12
25
11
25
8
25
13
25
15
25
11
25
12
25
10
25
9
25
13
25
9
25
6
25
13
|
56.00 |
|
44.00 |
|
24.00 |
|
36.00 |
|
56.00 |
|
40.00 |
|
40.00 |
|
48.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
60.00 |
|
44.00 |
|
48.00 |
|
40.00 |
|
36.00 |
|
52.00 |
|
36.00 |
|
24.00 |
|
52.00 |
|
1.3406
|
0.1408
|
-2.1131
|
-0.6919
|
1.3406
|
-0.2690
|
-0.2690
|
0.5426
|
0.1408
|
-1.1343
|
0.9411
|
1.7458
|
0.1408
|
0.5426
|
-0.2690
|
-0.6919
|
0.9411
|
-0.6919
|
-2.1131
|
0.9411
0.9252 |
0.9291 |
1.0661 |
0.9590 |
0.9252 |
0.9410 |
0.9410 |
0.9226 |
0.9291 |
0.9844 |
0.9213 |
0.9345 |
0.9291 |
0.9226 |
0.9410 |
0.9590 |
0.9213 |
0.9590 |
1.0661 |
0.9213 |
236
1 Examinee368
1.00 TEST0001
1 Examinee369
1.00 TEST0001
1 Examinee370
1.00 TEST0001
1 Examinee371
1.00 TEST0001
1 Examinee372
1.00 TEST0001
1 Examinee373
1.00 TEST0001
1 Examinee374
1.00 TEST0001
1 Examinee375
1.00 TEST0001
1 Examinee376
1.00 TEST0001
1 Examinee377
1.00 TEST0001
1 Examinee378
1.00 TEST0001
1 Examinee379
1.00 TEST0001
1 Examinee380
1.00 TEST0001
1 Examinee381
1.00 TEST0001
1 Examinee382
1.00 TEST0001
1 Examinee383
1.00 TEST0001
1 Examinee384
1.00 TEST0001
1 Examinee385
1.00 TEST0001
1 Examinee386
1.00 TEST0001
1 Examinee387
1.00 TEST0001
25
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25
13
25
8
25
10
25
11
25
8
25
9
25
10
25
11
25
12
25
3
25
7
25
8
25
13
25
7
25
11
25
13
25
15
25
10
25
9
|
48.00 |
|
52.00 |
|
32.00 |
|
40.00 |
|
44.00 |
|
32.00 |
|
36.00 |
|
40.00 |
|
44.00 |
|
48.00 |
|
12.00 |
|
28.00 |
|
32.00 |
|
52.00 |
|
28.00 |
|
44.00 |
|
52.00 |
|
60.00 |
|
40.00 |
|
36.00 |
|
0.5426 0.9226 |
|
0.9411 0.9213 |
|
-1.1343 0.9844 |
|
-0.2690 0.9410 |
|
0.1408 0.9291 |
|
-1.1343 0.9844 |
|
-0.6919 0.9590 |
|
-0.2690 0.9410 |
|
0.1408 0.9291 |
|
0.5426 0.9226 |
|
-4.0000 999.0000 |
|
-1.6043 1.0190 |
|
-1.1343 0.9844 |
|
0.9411 0.9213 |
|
-1.6043 1.0190 |
|
0.1408 0.9291 |
|
0.9411 0.9213 |
|
1.7458 0.9345 |
|
-0.2690 0.9410 |
|
-0.6919 0.9590 |
237
1 Examinee388
1.00 TEST0001
1 Examinee389
1.00 TEST0001
1 Examinee390
1.00 TEST0001
1 Examinee391
1.00 TEST0001
1 Examinee392
1.00 TEST0001
1 Examinee393
1.00 TEST0001
1 Examinee394
1.00 TEST0001
1 Examinee395
1.00 TEST0001
1 Examinee396
1.00 TEST0001
1 Examinee397
1.00 TEST0001
1 Examinee398
1.00 TEST0001
1 Examinee399
1.00 TEST0001
1 Examinee400
1.00 TEST0001
1 Examinee401
1.00 TEST0001
1 Examinee402
1.00 TEST0001
1 Examinee403
1.00 TEST0001
1 Examinee404
1.00 TEST0001
1 Examinee405
1.00 TEST0001
1 Examinee406
1.00 TEST0001
1 Examinee407
1.00 TEST0001
25
11
25
8
25
6
25
11
25
12
25
12
25
10
25
10
25
7
25
7
25
9
25
12
25
11
25
11
25
11
25
12
25
17
25
11
25
10
25
11
|
44.00 |
|
32.00 |
|
24.00 |
|
44.00 |
|
48.00 |
|
48.00 |
|
40.00 |
|
40.00 |
|
28.00 |
|
28.00 |
|
36.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
44.00 |
|
48.00 |
|
68.00 |
|
44.00 |
|
40.00 |
|
44.00 |
|
0.1408
|
-1.1343
|
-2.1131
|
0.1408
|
0.5426
|
0.5426
|
-0.2690
|
-0.2690
|
-1.6043
|
-1.6043
|
-0.6919
|
0.5426
|
0.1408
|
0.1408
|
0.1408
|
0.5426
|
2.5950
|
0.1408
|
-0.2690
|
0.1408
0.9291 |
0.9844 |
1.0661 |
0.9291 |
0.9226 |
0.9226 |
0.9410 |
0.9410 |
1.0190 |
1.0190 |
0.9590 |
0.9226 |
0.9291 |
0.9291 |
0.9291 |
0.9226 |
0.9729 |
0.9291 |
0.9410 |
0.9291 |
238
1 Examinee408
1.00 TEST0001
1 Examinee409
1.00 TEST0001
1 Examinee410
1.00 TEST0001
1 Examinee411
1.00 TEST0001
1 Examinee412
1.00 TEST0001
1 Examinee413
1.00 TEST0001
1 Examinee414
1.00 TEST0001
1 Examinee415
1.00 TEST0001
1 Examinee416
1.00 TEST0001
1 Examinee417
1.00 TEST0001
1 Examinee418
1.00 TEST0001
1 Examinee419
1.00 TEST0001
1 Examinee420
1.00 TEST0001
1 Examinee421
1.00 TEST0001
1 Examinee422
1.00 TEST0001
1 Examinee423
1.00 TEST0001
1 Examinee424
1.00 TEST0001
1 Examinee425
1.00 TEST0001
1 Examinee426
1.00 TEST0001
1 Examinee427
1.00 TEST0001
25
6
25
12
25
12
25
9
25
6
25
9
25
12
25
13
25
12
25
7
25
16
25
9
25
13
25
6
25
14
25
7
25
8
25
13
25
13
25
7
|
24.00 |
|
48.00 |
|
48.00 |
|
36.00 |
|
24.00 |
|
36.00 |
|
48.00 |
|
52.00 |
|
48.00 |
|
28.00 |
|
64.00 |
|
36.00 |
|
52.00 |
|
24.00 |
|
56.00 |
|
28.00 |
|
32.00 |
|
52.00 |
|
52.00 |
|
28.00 |
|
-2.1131
|
0.5426
|
0.5426
|
-0.6919
|
-2.1131
|
-0.6919
|
0.5426
|
0.9411
|
0.5426
|
-1.6043
|
2.1619
|
-0.6919
|
0.9411
|
-2.1131
|
1.3406
|
-1.6043
|
-1.1343
|
0.9411
|
0.9411
|
-1.6043
1.0661 |
0.9226 |
0.9226 |
0.9590 |
1.0661 |
0.9590 |
0.9226 |
0.9213 |
0.9226 |
1.0190 |
0.9500 |
0.9590 |
0.9213 |
1.0661 |
0.9252 |
1.0190 |
0.9844 |
0.9213 |
0.9213 |
1.0190 |
239
1 Examinee428
1.00 TEST0001
1 Examinee429
1.00 TEST0001
1 Examinee430
1.00 TEST0001
1 Examinee431
1.00 TEST0001
1 Examinee432
1.00 TEST0001
1 Examinee433
1.00 TEST0001
1 Examinee434
1.00 TEST0001
1 Examinee435
1.00 TEST0001
1 Examinee436
1.00 TEST0001
1 Examinee437
1.00 TEST0001
1 Examinee438
1.00 TEST0001
1 Examinee439
1.00 TEST0001
1 Examinee440
1.00 TEST0001
1 Examinee441
1.00 TEST0001
1 Examinee442
1.00 TEST0001
1 Examinee443
1.00 TEST0001
1 Examinee444
1.00 TEST0001
1 Examinee445
1.00 TEST0001
1 Examinee446
1.00 TEST0001
1 Examinee447
1.00 TEST0001
25
10
25
8
25
10
25
13
25
12
25
8
25
14
25
15
25
6
25
12
25
9
25
7
25
7
25
13
25
11
25
8
25
13
25
7
25
11
25
12
|
40.00 |
|
32.00 |
|
40.00 |
|
52.00 |
|
48.00 |
|
32.00 |
|
56.00 |
|
60.00 |
|
24.00 |
|
48.00 |
|
36.00 |
|
28.00 |
|
28.00 |
|
52.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
28.00 |
|
44.00 |
|
48.00 |
|
-0.2690
|
-1.1343
|
-0.2690
|
0.9411
|
0.5426
|
-1.1343
|
1.3406
|
1.7458
|
-2.1131
|
0.5426
|
-0.6919
|
-1.6043
|
-1.6043
|
0.9411
|
0.1408
|
-1.1343
|
0.9411
|
-1.6043
|
0.1408
|
0.5426
0.9410 |
0.9844 |
0.9410 |
0.9213 |
0.9226 |
0.9844 |
0.9252 |
0.9345 |
1.0661 |
0.9226 |
0.9590 |
1.0190 |
1.0190 |
0.9213 |
0.9291 |
0.9844 |
0.9213 |
1.0190 |
0.9291 |
0.9226 |
240
1 Examinee448
1.00 TEST0001
1 Examinee449
1.00 TEST0001
1 Examinee450
1.00 TEST0001
1 Examinee451
1.00 TEST0001
1 Examinee452
1.00 TEST0001
1 Examinee453
1.00 TEST0001
1 Examinee454
1.00 TEST0001
1 Examinee455
1.00 TEST0001
1 Examinee456
1.00 TEST0001
1 Examinee457
1.00 TEST0001
1 Examinee458
1.00 TEST0001
1 Examinee459
1.00 TEST0001
1 Examinee460
1.00 TEST0001
1 Examinee461
1.00 TEST0001
1 Examinee462
1.00 TEST0001
1 Examinee463
1.00 TEST0001
1 Examinee464
1.00 TEST0001
1 Examinee465
1.00 TEST0001
1 Examinee466
1.00 TEST0001
1 Examinee467
1.00 TEST0001
25
9
25
12
25
10
25
9
25
13
25
14
25
14
25
9
25
11
25
11
25
10
25
13
25
16
25
11
25
8
25
12
25
9
25
7
25
7
25
11
|
36.00 |
|
48.00 |
|
40.00 |
|
36.00 |
|
52.00 |
|
56.00 |
|
56.00 |
|
36.00 |
|
44.00 |
|
44.00 |
|
40.00 |
|
52.00 |
|
64.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
36.00 |
|
28.00 |
|
28.00 |
|
44.00 |
|
-0.6919
|
0.5426
|
-0.2690
|
-0.6919
|
0.9411
|
1.3406
|
1.3406
|
-0.6919
|
0.1408
|
0.1408
|
-0.2690
|
0.9411
|
2.1619
|
0.1408
|
-1.1343
|
0.5426
|
-0.6919
|
-1.6043
|
-1.6043
|
0.1408
0.9590 |
0.9226 |
0.9410 |
0.9590 |
0.9213 |
0.9252 |
0.9252 |
0.9590 |
0.9291 |
0.9291 |
0.9410 |
0.9213 |
0.9500 |
0.9291 |
0.9844 |
0.9226 |
0.9590 |
1.0190 |
1.0190 |
0.9291 |
241
1 Examinee468
1.00 TEST0001
1 Examinee469
1.00 TEST0001
1 Examinee470
1.00 TEST0001
1 Examinee471
1.00 TEST0001
1 Examinee472
1.00 TEST0001
1 Examinee473
1.00 TEST0001
1 Examinee474
1.00 TEST0001
1 Examinee475
1.00 TEST0001
1 Examinee476
1.00 TEST0001
1 Examinee477
1.00 TEST0001
1 Examinee478
1.00 TEST0001
1 Examinee479
1.00 TEST0001
1 Examinee480
1.00 TEST0001
1 Examinee481
1.00 TEST0001
1 Examinee482
1.00 TEST0001
1 Examinee483
1.00 TEST0001
1 Examinee484
1.00 TEST0001
1 Examinee485
1.00 TEST0001
1 Examinee486
1.00 TEST0001
1 Examinee487
1.00 TEST0001
25
18
25
10
25
8
25
12
25
10
25
10
25
10
25
9
25
11
25
8
25
12
25
8
25
9
25
10
25
11
25
10
25
12
25
16
25
10
25
11
|
72.00 |
|
40.00 |
|
32.00 |
|
48.00 |
|
40.00 |
|
40.00 |
|
40.00 |
|
36.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
32.00 |
|
36.00 |
|
40.00 |
|
44.00 |
|
40.00 |
|
48.00 |
|
64.00 |
|
40.00 |
|
44.00 |
|
3.0533
|
-0.2690
|
-1.1343
|
0.5426
|
-0.2690
|
-0.2690
|
-0.2690
|
-0.6919
|
0.1408
|
-1.1343
|
0.5426
|
-1.1343
|
-0.6919
|
-0.2690
|
0.1408
|
-0.2690
|
0.5426
|
2.1619
|
-0.2690
|
0.1408
1.0052 |
0.9410 |
0.9844 |
0.9226 |
0.9410 |
0.9410 |
0.9410 |
0.9590 |
0.9291 |
0.9844 |
0.9226 |
0.9844 |
0.9590 |
0.9410 |
0.9291 |
0.9410 |
0.9226 |
0.9500 |
0.9410 |
0.9291 |
242
1 Examinee488
1.00 TEST0001
1 Examinee489
1.00 TEST0001
1 Examinee490
1.00 TEST0001
1 Examinee491
1.00 TEST0001
1 Examinee492
1.00 TEST0001
1 Examinee493
1.00 TEST0001
1 Examinee494
1.00 TEST0001
1 Examinee495
1.00 TEST0001
1 Examinee496
1.00 TEST0001
1 Examinee497
1.00 TEST0001
1 Examinee498
1.00 TEST0001
1 Examinee499
1.00 TEST0001
1 Examinee500
1.00 TEST0001
1 Examinee501
1.00 TEST0001
1 Examinee502
1.00 TEST0001
1 Examinee503
1.00 TEST0001
1 Examinee504
1.00 TEST0001
1 Examinee505
1.00 TEST0001
1 Examinee506
1.00 TEST0001
1 Examinee507
1.00 TEST0001
25
9
25
14
25
13
25
14
25
14
25
17
25
13
25
6
25
16
25
12
25
7
25
13
25
10
25
12
25
10
25
6
25
9
25
19
25
14
25
15
|
36.00 |
|
56.00 |
|
52.00 |
|
56.00 |
|
56.00 |
|
68.00 |
|
52.00 |
|
24.00 |
|
64.00 |
|
48.00 |
|
28.00 |
|
52.00 |
|
40.00 |
|
48.00 |
|
40.00 |
|
24.00 |
|
36.00 |
|
76.00 |
|
56.00 |
|
60.00 |
|
-0.6919
|
1.3406
|
0.9411
|
1.3406
|
1.3406
|
2.5950
|
0.9411
|
-2.1131
|
2.1619
|
0.5426
|
-1.6043
|
0.9411
|
-0.2690
|
0.5426
|
-0.2690
|
-2.1131
|
-0.6919
|
3.5477
|
1.3406
|
1.7458
0.9590 |
0.9252 |
0.9213 |
0.9252 |
0.9252 |
0.9729 |
0.9213 |
1.0661 |
0.9500 |
0.9226 |
1.0190 |
0.9213 |
0.9410 |
0.9226 |
0.9410 |
1.0661 |
0.9590 |
1.0503 |
0.9252 |
0.9345 |
243
1 Examinee508
1.00 TEST0001
1 Examinee509
1.00 TEST0001
1 Examinee510
1.00 TEST0001
1 Examinee511
1.00 TEST0001
1 Examinee512
1.00 TEST0001
1 Examinee513
1.00 TEST0001
1 Examinee514
1.00 TEST0001
1 Examinee515
1.00 TEST0001
1 Examinee516
1.00 TEST0001
1 Examinee517
1.00 TEST0001
1 Examinee518
1.00 TEST0001
1 Examinee519
1.00 TEST0001
1 Examinee520
1.00 TEST0001
1 Examinee521
1.00 TEST0001
1 Examinee522
1.00 TEST0001
1 Examinee523
1.00 TEST0001
1 Examinee524
1.00 TEST0001
1 Examinee525
1.00 TEST0001
1 Examinee526
1.00 TEST0001
1 Examinee527
1.00 TEST0001
25
15
25
12
25
13
25
12
25
12
25
12
25
12
25
12
25
6
25
14
25
13
25
10
25
10
25
11
25
8
25
13
25
13
25
17
25
9
25
8
|
60.00 |
|
48.00 |
|
52.00 |
|
48.00 |
|
48.00 |
|
48.00 |
|
48.00 |
|
48.00 |
|
24.00 |
|
56.00 |
|
52.00 |
|
40.00 |
|
40.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
52.00 |
|
68.00 |
|
36.00 |
|
32.00 |
|
1.7458
|
0.5426
|
0.9411
|
0.5426
|
0.5426
|
0.5426
|
0.5426
|
0.5426
|
-2.1131
|
1.3406
|
0.9411
|
-0.2690
|
-0.2690
|
0.1408
|
-1.1343
|
0.9411
|
0.9411
|
2.5950
|
-0.6919
|
-1.1343
0.9345 |
0.9226 |
0.9213 |
0.9226 |
0.9226 |
0.9226 |
0.9226 |
0.9226 |
1.0661 |
0.9252 |
0.9213 |
0.9410 |
0.9410 |
0.9291 |
0.9844 |
0.9213 |
0.9213 |
0.9729 |
0.9590 |
0.9844 |
244
1 Examinee528
1.00 TEST0001
1 Examinee529
1.00 TEST0001
1 Examinee530
1.00 TEST0001
1 Examinee531
1.00 TEST0001
1 Examinee532
1.00 TEST0001
1 Examinee533
1.00 TEST0001
1 Examinee534
1.00 TEST0001
1 Examinee535
1.00 TEST0001
1 Examinee536
1.00 TEST0001
1 Examinee537
1.00 TEST0001
1 Examinee538
1.00 TEST0001
1 Examinee539
1.00 TEST0001
1 Examinee540
1.00 TEST0001
1 Examinee541
1.00 TEST0001
1 Examinee542
1.00 TEST0001
1 Examinee543
1.00 TEST0001
1 Examinee544
1.00 TEST0001
1 Examinee545
1.00 TEST0001
1 Examinee546
1.00 TEST0001
1 Examinee547
1.00 TEST0001
25
10
25
8
25
9
25
5
25
11
25
11
25
9
25
12
25
9
25
12
25
8
25
13
25
7
25
15
25
16
25
9
25
10
25
10
25
13
25
7
|
40.00 |
|
32.00 |
|
36.00 |
|
20.00 |
|
44.00 |
|
44.00 |
|
36.00 |
|
48.00 |
|
36.00 |
|
48.00 |
|
32.00 |
|
52.00 |
|
28.00 |
|
60.00 |
|
64.00 |
|
36.00 |
|
40.00 |
|
40.00 |
|
52.00 |
|
28.00 |
|
-0.2690
|
-1.1343
|
-0.6919
|
-2.6776
|
0.1408
|
0.1408
|
-0.6919
|
0.5426
|
-0.6919
|
0.5426
|
-1.1343
|
0.9411
|
-1.6043
|
1.7458
|
2.1619
|
-0.6919
|
-0.2690
|
-0.2690
|
0.9411
|
-1.6043
0.9410 |
0.9844 |
0.9590 |
1.1311 |
0.9291 |
0.9291 |
0.9590 |
0.9226 |
0.9590 |
0.9226 |
0.9844 |
0.9213 |
1.0190 |
0.9345 |
0.9500 |
0.9590 |
0.9410 |
0.9410 |
0.9213 |
1.0190 |
245
1 Examinee548
1.00 TEST0001
1 Examinee549
1.00 TEST0001
1 Examinee550
1.00 TEST0001
1 Examinee551
1.00 TEST0001
1 Examinee552
1.00 TEST0001
1 Examinee553
1.00 TEST0001
1 Examinee554
1.00 TEST0001
1 Examinee555
1.00 TEST0001
1 Examinee556
1.00 TEST0001
1 Examinee557
1.00 TEST0001
1 Examinee558
1.00 TEST0001
1 Examinee559
1.00 TEST0001
1 Examinee560
1.00 TEST0001
1 Examinee561
1.00 TEST0001
1 Examinee562
1.00 TEST0001
1 Examinee563
1.00 TEST0001
1 Examinee564
1.00 TEST0001
1 Examinee565
1.00 TEST0001
1 Examinee566
1.00 TEST0001
1 Examinee567
1.00 TEST0001
25
5
25
10
25
4
25
4
25
6
25
6
25
5
25
7
25
7
25
2
25
3
25
6
25
2
25
5
25
8
25
7
25
8
25
9
25
8
25
9
|
|
20.00 | -2.6776 1.1311 |
|
|
40.00 | -0.2690 0.9410 |
|
|
16.00 | -3.3255 1.2245 |
|
|
16.00 | -3.3255 1.2245 |
|
|
24.00 | -2.1131 1.0661 |
|
|
24.00 | -2.1131 1.0661 |
|
|
20.00 | -2.6776 1.1311 |
|
|
28.00 | -1.6043 1.0190 |
|
|
28.00 | -1.6043 1.0190 |
|
|
8.00 | -4.0000 999.0000 |
|
|
12.00 | -4.0000 999.0000 |
|
|
24.00 | -2.1131 1.0661 |
|
|
8.00 | -4.0000 999.0000 |
|
|
20.00 | -2.6776 1.1311 |
|
|
32.00 | -1.1343 0.9844 |
|
|
28.00 | -1.6043 1.0190 |
|
|
32.00 | -1.1343 0.9844 |
|
|
36.00 | -0.6919 0.9590 |
|
|
32.00 | -1.1343 0.9844 |
|
|
36.00 | -0.6919 0.9590 |
246
1 Examinee568
1.00 TEST0001
1 Examinee569
1.00 TEST0001
1 Examinee570
1.00 TEST0001
1 Examinee571
1.00 TEST0001
1 Examinee572
1.00 TEST0001
1 Examinee573
1.00 TEST0001
1 Examinee574
1.00 TEST0001
1 Examinee575
1.00 TEST0001
1 Examinee576
1.00 TEST0001
1 Examinee577
1.00 TEST0001
1 Examinee578
1.00 TEST0001
1 Examinee579
1.00 TEST0001
1 Examinee580
1.00 TEST0001
1 Examinee581
1.00 TEST0001
1 Examinee582
1.00 TEST0001
1 Examinee583
1.00 TEST0001
1 Examinee584
1.00 TEST0001
1 Examinee585
1.00 TEST0001
1 Examinee586
1.00 TEST0001
1 Examinee587
1.00 TEST0001
25
3
25
4
25
7
25
5
25
3
25
6
25
4
25
8
25
2
25
3
25
10
25
1
25
10
25
8
25
12
25
8
25
10
25
14
25
9
25
12
|
|
12.00 | -4.0000 999.0000 |
|
|
16.00 | -3.3255 1.2245 |
|
|
28.00 | -1.6043 1.0190 |
|
|
20.00 | -2.6776 1.1311 |
|
|
12.00 | -4.0000 999.0000 |
|
|
24.00 | -2.1131 1.0661 |
|
|
16.00 | -3.3255 1.2245 |
|
|
32.00 | -1.1343 0.9844 |
|
|
8.00 | -4.0000 999.0000 |
|
|
12.00 | -4.0000 999.0000 |
|
|
40.00 | -0.2690 0.9410 |
|
|
4.00 | -4.0000 999.0000 |
|
|
40.00 | -0.2690 0.9410 |
|
|
32.00 | -1.1343 0.9844 |
|
|
48.00 | 0.5426 0.9226 |
|
|
32.00 | -1.1343 0.9844 |
|
|
40.00 | -0.2690 0.9410 |
|
|
56.00 | 1.3406 0.9252 |
|
|
36.00 | -0.6919 0.9590 |
|
|
48.00 | 0.5426 0.9226 |
247
1 Examinee588
1.00 TEST0001
1 Examinee589
1.00 TEST0001
1 Examinee590
1.00 TEST0001
1 Examinee591
1.00 TEST0001
1 Examinee592
1.00 TEST0001
1 Examinee593
1.00 TEST0001
1 Examinee594
1.00 TEST0001
1 Examinee595
1.00 TEST0001
1 Examinee596
1.00 TEST0001
1 Examinee597
1.00 TEST0001
1 Examinee598
1.00 TEST0001
1 Examinee599
1.00 TEST0001
1 Examinee600
1.00 TEST0001
1 Examinee601
1.00 TEST0001
1 Examinee602
1.00 TEST0001
1 Examinee603
1.00 TEST0001
1 Examinee604
1.00 TEST0001
1 Examinee605
1.00 TEST0001
1 Examinee606
1.00 TEST0001
1 Examinee607
1.00 TEST0001
25
12
25
14
25
8
25
13
25
7
25
15
25
12
25
12
25
8
25
14
25
7
25
8
25
11
25
9
25
12
25
9
25
12
25
8
25
7
25
10
|
48.00 |
|
56.00 |
|
32.00 |
|
52.00 |
|
28.00 |
|
60.00 |
|
48.00 |
|
48.00 |
|
32.00 |
|
56.00 |
|
28.00 |
|
32.00 |
|
44.00 |
|
36.00 |
|
48.00 |
|
36.00 |
|
48.00 |
|
32.00 |
|
28.00 |
|
40.00 |
|
0.5426
|
1.3406
|
-1.1343
|
0.9411
|
-1.6043
|
1.7458
|
0.5426
|
0.5426
|
-1.1343
|
1.3406
|
-1.6043
|
-1.1343
|
0.1408
|
-0.6919
|
0.5426
|
-0.6919
|
0.5426
|
-1.1343
|
-1.6043
|
-0.2690
0.9226 |
0.9252 |
0.9844 |
0.9213 |
1.0190 |
0.9345 |
0.9226 |
0.9226 |
0.9844 |
0.9252 |
1.0190 |
0.9844 |
0.9291 |
0.9590 |
0.9226 |
0.9590 |
0.9226 |
0.9844 |
1.0190 |
0.9410 |
248
1 Examinee608
1.00 TEST0001
1 Examinee609
1.00 TEST0001
1 Examinee610
1.00 TEST0001
1 Examinee611
1.00 TEST0001
1 Examinee612
1.00 TEST0001
1 Examinee613
1.00 TEST0001
1 Examinee614
1.00 TEST0001
1 Examinee615
1.00 TEST0001
1 Examinee616
1.00 TEST0001
1 Examinee617
1.00 TEST0001
1 Examinee618
1.00 TEST0001
1 Examinee619
1.00 TEST0001
1 Examinee620
1.00 TEST0001
1 Examinee621
1.00 TEST0001
1 Examinee622
1.00 TEST0001
1 Examinee623
1.00 TEST0001
1 Examinee624
1.00 TEST0001
1 Examinee625
1.00 TEST0001
1 Examinee626
1.00 TEST0001
1 Examinee627
1.00 TEST0001
25
6
25
13
25
9
25
13
25
2
25
13
25
11
25
12
25
8
25
13
25
15
25
10
25
8
25
8
25
10
25
9
25
14
25
11
25
11
25
16
|
|
24.00 | -2.1131 1.0661 |
|
|
52.00 | 0.9411 0.9213 |
|
|
36.00 | -0.6919 0.9590 |
|
|
52.00 | 0.9411 0.9213 |
|
|
8.00 | -4.0000 999.0000 |
|
|
52.00 | 0.9411 0.9213 |
|
|
44.00 | 0.1408 0.9291 |
|
|
48.00 | 0.5426 0.9226 |
|
|
32.00 | -1.1343 0.9844 |
|
|
52.00 | 0.9411 0.9213 |
|
|
60.00 | 1.7458 0.9345 |
|
|
40.00 | -0.2690 0.9410 |
|
|
32.00 | -1.1343 0.9844 |
|
|
32.00 | -1.1343 0.9844 |
|
|
40.00 | -0.2690 0.9410 |
|
|
36.00 | -0.6919 0.9590 |
|
|
56.00 | 1.3406 0.9252 |
|
|
44.00 | 0.1408 0.9291 |
|
|
44.00 | 0.1408 0.9291 |
|
|
64.00 | 2.1619 0.9500 |
249
1 Examinee628
1.00 TEST0001
1 Examinee629
1.00 TEST0001
1 Examinee630
1.00 TEST0001
1 Examinee631
1.00 TEST0001
1 Examinee632
1.00 TEST0001
1 Examinee633
1.00 TEST0001
1 Examinee634
1.00 TEST0001
1 Examinee635
1.00 TEST0001
1 Examinee636
1.00 TEST0001
1 Examinee637
1.00 TEST0001
1 Examinee638
1.00 TEST0001
1 Examinee639
1.00 TEST0001
1 Examinee640
1.00 TEST0001
1 Examinee641
1.00 TEST0001
1 Examinee642
1.00 TEST0001
1 Examinee643
1.00 TEST0001
1 Examinee644
1.00 TEST0001
1 Examinee645
1.00 TEST0001
1 Examinee646
1.00 TEST0001
1 Examinee647
1.00 TEST0001
25
10
25
6
25
9
25
14
25
11
25
15
25
8
25
12
25
12
25
13
25
18
25
10
25
11
25
12
25
9
25
6
25
15
25
8
25
6
25
7
|
40.00 |
|
24.00 |
|
36.00 |
|
56.00 |
|
44.00 |
|
60.00 |
|
32.00 |
|
48.00 |
|
48.00 |
|
52.00 |
|
72.00 |
|
40.00 |
|
44.00 |
|
48.00 |
|
36.00 |
|
24.00 |
|
60.00 |
|
32.00 |
|
24.00 |
|
28.00 |
|
-0.2690
|
-2.1131
|
-0.6919
|
1.3406
|
0.1408
|
1.7458
|
-1.1343
|
0.5426
|
0.5426
|
0.9411
|
3.0533
|
-0.2690
|
0.1408
|
0.5426
|
-0.6919
|
-2.1131
|
1.7458
|
-1.1343
|
-2.1131
|
-1.6043
0.9410 |
1.0661 |
0.9590 |
0.9252 |
0.9291 |
0.9345 |
0.9844 |
0.9226 |
0.9226 |
0.9213 |
1.0052 |
0.9410 |
0.9291 |
0.9226 |
0.9590 |
1.0661 |
0.9345 |
0.9844 |
1.0661 |
1.0190 |
250
1 Examinee648
1.00 TEST0001
1 Examinee649
1.00 TEST0001
1 Examinee650
1.00 TEST0001
1 Examinee651
1.00 TEST0001
1 Examinee652
1.00 TEST0001
1 Examinee653
1.00 TEST0001
1 Examinee654
1.00 TEST0001
1 Examinee655
1.00 TEST0001
1 Examinee656
1.00 TEST0001
1 Examinee657
1.00 TEST0001
1 Examinee658
1.00 TEST0001
1 Examinee659
1.00 TEST0001
1 Examinee660
1.00 TEST0001
1 Examinee661
1.00 TEST0001
1 Examinee662
1.00 TEST0001
1 Examinee663
1.00 TEST0001
1 Examinee664
1.00 TEST0001
1 Examinee665
1.00 TEST0001
1 Examinee666
1.00 TEST0001
1 Examinee667
1.00 TEST0001
25
8
25
13
25
9
25
15
25
8
25
17
25
19
25
6
25
8
25
10
25
13
25
6
25
14
25
8
25
9
25
8
25
12
25
6
25
10
25
9
|
32.00 |
|
52.00 |
|
36.00 |
|
60.00 |
|
32.00 |
|
68.00 |
|
76.00 |
|
24.00 |
|
32.00 |
|
40.00 |
|
52.00 |
|
24.00 |
|
56.00 |
|
32.00 |
|
36.00 |
|
32.00 |
|
48.00 |
|
24.00 |
|
40.00 |
|
36.00 |
|
-1.1343
|
0.9411
|
-0.6919
|
1.7458
|
-1.1343
|
2.5950
|
3.5477
|
-2.1131
|
-1.1343
|
-0.2690
|
0.9411
|
-2.1131
|
1.3406
|
-1.1343
|
-0.6919
|
-1.1343
|
0.5426
|
-2.1131
|
-0.2690
|
-0.6919
0.9844 |
0.9213 |
0.9590 |
0.9345 |
0.9844 |
0.9729 |
1.0503 |
1.0661 |
0.9844 |
0.9410 |
0.9213 |
1.0661 |
0.9252 |
0.9844 |
0.9590 |
0.9844 |
0.9226 |
1.0661 |
0.9410 |
0.9590 |
251
1 Examinee668
1.00 TEST0001
1 Examinee669
1.00 TEST0001
1 Examinee670
1.00 TEST0001
1 Examinee671
1.00 TEST0001
1 Examinee672
1.00 TEST0001
1 Examinee673
1.00 TEST0001
1 Examinee674
1.00 TEST0001
1 Examinee675
1.00 TEST0001
1 Examinee676
1.00 TEST0001
1 Examinee677
1.00 TEST0001
1 Examinee678
1.00 TEST0001
1 Examinee679
1.00 TEST0001
1 Examinee680
1.00 TEST0001
1 Examinee681
1.00 TEST0001
1 Examinee682
1.00 TEST0001
1 Examinee683
1.00 TEST0001
1 Examinee684
1.00 TEST0001
1 Examinee685
1.00 TEST0001
1 Examinee686
1.00 TEST0001
1 Examinee687
1.00 TEST0001
25
12
25
9
25
13
25
17
25
13
25
16
25
11
25
10
25
15
25
12
25
13
25
10
25
15
25
6
25
14
25
10
25
14
25
13
25
5
25
9
|
48.00 |
|
36.00 |
|
52.00 |
|
68.00 |
|
52.00 |
|
64.00 |
|
44.00 |
|
40.00 |
|
60.00 |
|
48.00 |
|
52.00 |
|
40.00 |
|
60.00 |
|
24.00 |
|
56.00 |
|
40.00 |
|
56.00 |
|
52.00 |
|
20.00 |
|
36.00 |
|
0.5426
|
-0.6919
|
0.9411
|
2.5950
|
0.9411
|
2.1619
|
0.1408
|
-0.2690
|
1.7458
|
0.5426
|
0.9411
|
-0.2690
|
1.7458
|
-2.1131
|
1.3406
|
-0.2690
|
1.3406
|
0.9411
|
-2.6776
|
-0.6919
0.9226 |
0.9590 |
0.9213 |
0.9729 |
0.9213 |
0.9500 |
0.9291 |
0.9410 |
0.9345 |
0.9226 |
0.9213 |
0.9410 |
0.9345 |
1.0661 |
0.9252 |
0.9410 |
0.9252 |
0.9213 |
1.1311 |
0.9590 |
252
1 Examinee688
1.00 TEST0001
1 Examinee689
1.00 TEST0001
1 Examinee690
1.00 TEST0001
1 Examinee691
1.00 TEST0001
1 Examinee692
1.00 TEST0001
1 Examinee693
1.00 TEST0001
1 Examinee694
1.00 TEST0001
1 Examinee695
1.00 TEST0001
1 Examinee696
1.00 TEST0001
1 Examinee697
1.00 TEST0001
1 Examinee698
1.00 TEST0001
1 Examinee699
1.00 TEST0001
1 Examinee700
1.00 TEST0001
1 Examinee701
1.00 TEST0001
1 Examinee702
1.00 TEST0001
1 Examinee703
1.00 TEST0001
1 Examinee704
1.00 TEST0001
1 Examinee705
1.00 TEST0001
1 Examinee706
1.00 TEST0001
1 Examinee707
1.00 TEST0001
25
16
25
8
25
16
25
13
25
8
25
11
25
10
25
14
25
8
25
9
25
11
25
7
25
7
25
13
25
10
25
7
25
10
25
8
25
11
25
11
|
64.00 |
|
32.00 |
|
64.00 |
|
52.00 |
|
32.00 |
|
44.00 |
|
40.00 |
|
56.00 |
|
32.00 |
|
36.00 |
|
44.00 |
|
28.00 |
|
28.00 |
|
52.00 |
|
40.00 |
|
28.00 |
|
40.00 |
|
32.00 |
|
44.00 |
|
44.00 |
|
2.1619
|
-1.1343
|
2.1619
|
0.9411
|
-1.1343
|
0.1408
|
-0.2690
|
1.3406
|
-1.1343
|
-0.6919
|
0.1408
|
-1.6043
|
-1.6043
|
0.9411
|
-0.2690
|
-1.6043
|
-0.2690
|
-1.1343
|
0.1408
|
0.1408
0.9500 |
0.9844 |
0.9500 |
0.9213 |
0.9844 |
0.9291 |
0.9410 |
0.9252 |
0.9844 |
0.9590 |
0.9291 |
1.0190 |
1.0190 |
0.9213 |
0.9410 |
1.0190 |
0.9410 |
0.9844 |
0.9291 |
0.9291 |
253
1 Examinee708
1.00 TEST0001
1 Examinee709
1.00 TEST0001
1 Examinee710
1.00 TEST0001
1 Examinee711
1.00 TEST0001
1 Examinee712
1.00 TEST0001
1 Examinee713
1.00 TEST0001
1 Examinee714
1.00 TEST0001
1 Examinee715
1.00 TEST0001
1 Examinee716
1.00 TEST0001
1 Examinee717
1.00 TEST0001
1 Examinee718
1.00 TEST0001
1 Examinee719
1.00 TEST0001
1 Examinee720
1.00 TEST0001
1 Examinee721
1.00 TEST0001
1 Examinee722
1.00 TEST0001
1 Examinee723
1.00 TEST0001
1 Examinee724
1.00 TEST0001
1 Examinee725
1.00 TEST0001
1 Examinee726
1.00 TEST0001
1 Examinee727
1.00 TEST0001
25
15
25
13
25
14
25
13
25
10
25
14
25
9
25
11
25
10
25
10
25
13
25
11
25
11
25
17
25
9
25
11
25
13
25
5
25
12
25
10
|
60.00 |
|
52.00 |
|
56.00 |
|
52.00 |
|
40.00 |
|
56.00 |
|
36.00 |
|
44.00 |
|
40.00 |
|
40.00 |
|
52.00 |
|
44.00 |
|
44.00 |
|
68.00 |
|
36.00 |
|
44.00 |
|
52.00 |
|
20.00 |
|
48.00 |
|
40.00 |
|
1.7458
|
0.9411
|
1.3406
|
0.9411
|
-0.2690
|
1.3406
|
-0.6919
|
0.1408
|
-0.2690
|
-0.2690
|
0.9411
|
0.1408
|
0.1408
|
2.5950
|
-0.6919
|
0.1408
|
0.9411
|
-2.6776
|
0.5426
|
-0.2690
0.9345 |
0.9213 |
0.9252 |
0.9213 |
0.9410 |
0.9252 |
0.9590 |
0.9291 |
0.9410 |
0.9410 |
0.9213 |
0.9291 |
0.9291 |
0.9729 |
0.9590 |
0.9291 |
0.9213 |
1.1311 |
0.9226 |
0.9410 |
254
1 Examinee728
1.00 TEST0001
1 Examinee729
1.00 TEST0001
1 Examinee730
1.00 TEST0001
1 Examinee731
1.00 TEST0001
1 Examinee732
1.00 TEST0001
1 Examinee733
1.00 TEST0001
1 Examinee734
1.00 TEST0001
1 Examinee735
1.00 TEST0001
1 Examinee736
1.00 TEST0001
1 Examinee737
1.00 TEST0001
1 Examinee738
1.00 TEST0001
1 Examinee739
1.00 TEST0001
1 Examinee740
1.00 TEST0001
1 Examinee741
1.00 TEST0001
1 Examinee742
1.00 TEST0001
1 Examinee743
1.00 TEST0001
1 Examinee744
1.00 TEST0001
1 Examinee745
1.00 TEST0001
1 Examinee746
1.00 TEST0001
1 Examinee747
1.00 TEST0001
25
11
25
11
25
7
25
13
25
14
25
12
25
12
25
12
25
9
25
13
25
7
25
13
25
9
25
11
25
8
25
12
25
14
25
14
25
11
25
11
|
44.00 |
|
44.00 |
|
28.00 |
|
52.00 |
|
56.00 |
|
48.00 |
|
48.00 |
|
48.00 |
|
36.00 |
|
52.00 |
|
28.00 |
|
52.00 |
|
36.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
56.00 |
|
56.00 |
|
44.00 |
|
44.00 |
|
0.1408
|
0.1408
|
-1.6043
|
0.9411
|
1.3406
|
0.5426
|
0.5426
|
0.5426
|
-0.6919
|
0.9411
|
-1.6043
|
0.9411
|
-0.6919
|
0.1408
|
-1.1343
|
0.5426
|
1.3406
|
1.3406
|
0.1408
|
0.1408
0.9291 |
0.9291 |
1.0190 |
0.9213 |
0.9252 |
0.9226 |
0.9226 |
0.9226 |
0.9590 |
0.9213 |
1.0190 |
0.9213 |
0.9590 |
0.9291 |
0.9844 |
0.9226 |
0.9252 |
0.9252 |
0.9291 |
0.9291 |
255
1 Examinee748
1.00 TEST0001
1 Examinee749
1.00 TEST0001
1 Examinee750
1.00 TEST0001
1 Examinee751
1.00 TEST0001
1 Examinee752
1.00 TEST0001
1 Examinee753
1.00 TEST0001
1 Examinee754
1.00 TEST0001
1 Examinee755
1.00 TEST0001
1 Examinee756
1.00 TEST0001
1 Examinee757
1.00 TEST0001
1 Examinee758
1.00 TEST0001
1 Examinee759
1.00 TEST0001
1 Examinee760
1.00 TEST0001
1 Examinee761
1.00 TEST0001
1 Examinee762
1.00 TEST0001
1 Examinee763
1.00 TEST0001
1 Examinee764
1.00 TEST0001
1 Examinee765
1.00 TEST0001
1 Examinee766
1.00 TEST0001
1 Examinee767
1.00 TEST0001
25
10
25
9
25
12
25
4
25
12
25
5
25
11
25
9
25
13
25
5
25
13
25
11
25
4
25
13
25
9
25
10
25
8
25
8
25
11
25
10
|
40.00 |
|
36.00 |
|
48.00 |
|
16.00 |
|
48.00 |
|
20.00 |
|
44.00 |
|
36.00 |
|
52.00 |
|
20.00 |
|
52.00 |
|
44.00 |
|
16.00 |
|
52.00 |
|
36.00 |
|
40.00 |
|
32.00 |
|
32.00 |
|
44.00 |
|
40.00 |
|
-0.2690
|
-0.6919
|
0.5426
|
-3.3255
|
0.5426
|
-2.6776
|
0.1408
|
-0.6919
|
0.9411
|
-2.6776
|
0.9411
|
0.1408
|
-3.3255
|
0.9411
|
-0.6919
|
-0.2690
|
-1.1343
|
-1.1343
|
0.1408
|
-0.2690
0.9410 |
0.9590 |
0.9226 |
1.2245 |
0.9226 |
1.1311 |
0.9291 |
0.9590 |
0.9213 |
1.1311 |
0.9213 |
0.9291 |
1.2245 |
0.9213 |
0.9590 |
0.9410 |
0.9844 |
0.9844 |
0.9291 |
0.9410 |
256
1 Examinee768
1.00 TEST0001
1 Examinee769
1.00 TEST0001
1 Examinee770
1.00 TEST0001
1 Examinee771
1.00 TEST0001
1 Examinee772
1.00 TEST0001
1 Examinee773
1.00 TEST0001
1 Examinee774
1.00 TEST0001
1 Examinee775
1.00 TEST0001
1 Examinee776
1.00 TEST0001
1 Examinee777
1.00 TEST0001
1 Examinee778
1.00 TEST0001
1 Examinee779
1.00 TEST0001
1 Examinee780
1.00 TEST0001
1 Examinee781
1.00 TEST0001
1 Examinee782
1.00 TEST0001
1 Examinee783
1.00 TEST0001
1 Examinee784
1.00 TEST0001
1 Examinee785
1.00 TEST0001
1 Examinee786
1.00 TEST0001
1 Examinee787
1.00 TEST0001
25
6
25
10
25
19
25
14
25
19
25
13
25
11
25
11
25
12
25
15
25
11
25
14
25
14
25
5
25
10
25
15
25
9
25
4
25
7
25
10
|
24.00 |
|
40.00 |
|
76.00 |
|
56.00 |
|
76.00 |
|
52.00 |
|
44.00 |
|
44.00 |
|
48.00 |
|
60.00 |
|
44.00 |
|
56.00 |
|
56.00 |
|
20.00 |
|
40.00 |
|
60.00 |
|
36.00 |
|
16.00 |
|
28.00 |
|
40.00 |
|
-2.1131
|
-0.2690
|
3.5477
|
1.3406
|
3.5477
|
0.9411
|
0.1408
|
0.1408
|
0.5426
|
1.7458
|
0.1408
|
1.3406
|
1.3406
|
-2.6776
|
-0.2690
|
1.7458
|
-0.6919
|
-3.3255
|
-1.6043
|
-0.2690
1.0661 |
0.9410 |
1.0503 |
0.9252 |
1.0503 |
0.9213 |
0.9291 |
0.9291 |
0.9226 |
0.9345 |
0.9291 |
0.9252 |
0.9252 |
1.1311 |
0.9410 |
0.9345 |
0.9590 |
1.2245 |
1.0190 |
0.9410 |
257
1 Examinee788
1.00 TEST0001
1 Examinee789
1.00 TEST0001
1 Examinee790
1.00 TEST0001
1 Examinee791
1.00 TEST0001
1 Examinee792
1.00 TEST0001
1 Examinee793
1.00 TEST0001
1 Examinee794
1.00 TEST0001
1 Examinee795
1.00 TEST0001
1 Examinee796
1.00 TEST0001
1 Examinee797
1.00 TEST0001
1 Examinee798
1.00 TEST0001
1 Examinee799
1.00 TEST0001
1 Examinee800
1.00 TEST0001
1 Examinee801
1.00 TEST0001
1 Examinee802
1.00 TEST0001
1 Examinee803
1.00 TEST0001
1 Examinee804
1.00 TEST0001
1 Examinee805
1.00 TEST0001
1 Examinee806
1.00 TEST0001
1 Examinee807
1.00 TEST0001
25
14
25
16
25
12
25
14
25
9
25
7
25
12
25
9
25
9
25
12
25
9
25
10
25
14
25
12
25
16
25
14
25
14
25
17
25
17
25
17
|
56.00 |
|
64.00 |
|
48.00 |
|
56.00 |
|
36.00 |
|
28.00 |
|
48.00 |
|
36.00 |
|
36.00 |
|
48.00 |
|
36.00 |
|
40.00 |
|
56.00 |
|
48.00 |
|
64.00 |
|
56.00 |
|
56.00 |
|
68.00 |
|
68.00 |
|
68.00 |
|
1.3406
|
2.1619
|
0.5426
|
1.3406
|
-0.6919
|
-1.6043
|
0.5426
|
-0.6919
|
-0.6919
|
0.5426
|
-0.6919
|
-0.2690
|
1.3406
|
0.5426
|
2.1619
|
1.3406
|
1.3406
|
2.5950
|
2.5950
|
2.5950
0.9252 |
0.9500 |
0.9226 |
0.9252 |
0.9590 |
1.0190 |
0.9226 |
0.9590 |
0.9590 |
0.9226 |
0.9590 |
0.9410 |
0.9252 |
0.9226 |
0.9500 |
0.9252 |
0.9252 |
0.9729 |
0.9729 |
0.9729 |
258
1 Examinee808
1.00 TEST0001
1 Examinee809
1.00 TEST0001
1 Examinee810
1.00 TEST0001
1 Examinee811
1.00 TEST0001
1 Examinee812
1.00 TEST0001
1 Examinee813
1.00 TEST0001
1 Examinee814
1.00 TEST0001
1 Examinee815
1.00 TEST0001
1 Examinee816
1.00 TEST0001
1 Examinee817
1.00 TEST0001
1 Examinee818
1.00 TEST0001
1 Examinee819
1.00 TEST0001
1 Examinee820
1.00 TEST0001
1 Examinee821
1.00 TEST0001
1 Examinee822
1.00 TEST0001
1 Examinee823
1.00 TEST0001
1 Examinee824
1.00 TEST0001
1 Examinee825
1.00 TEST0001
1 Examinee826
1.00 TEST0001
1 Examinee827
1.00 TEST0001
25
5
25
14
25
14
25
19
25
3
25
15
25
14
25
8
25
9
25
2
25
7
25
3
25
3
25
5
25
9
25
7
25
8
25
6
25
6
25
4
|
|
20.00 | -2.6776 1.1311 |
|
|
56.00 | 1.3406 0.9252 |
|
|
56.00 | 1.3406 0.9252 |
|
|
76.00 | 3.5477 1.0503 |
|
|
12.00 | -4.0000 999.0000 |
|
|
60.00 | 1.7458 0.9345 |
|
|
56.00 | 1.3406 0.9252 |
|
|
32.00 | -1.1343 0.9844 |
|
|
36.00 | -0.6919 0.9590 |
|
|
8.00 | -4.0000 999.0000 |
|
|
28.00 | -1.6043 1.0190 |
|
|
12.00 | -4.0000 999.0000 |
|
|
12.00 | -4.0000 999.0000 |
|
|
20.00 | -2.6776 1.1311 |
|
|
36.00 | -0.6919 0.9590 |
|
|
28.00 | -1.6043 1.0190 |
|
|
32.00 | -1.1343 0.9844 |
|
|
24.00 | -2.1131 1.0661 |
|
|
24.00 | -2.1131 1.0661 |
|
|
16.00 | -3.3255 1.2245 |
259
1 Examinee828
1.00 TEST0001
1 Examinee829
1.00 TEST0001
1 Examinee830
1.00 TEST0001
1 Examinee831
1.00 TEST0001
1 Examinee832
1.00 TEST0001
1 Examinee833
1.00 TEST0001
1 Examinee834
1.00 TEST0001
1 Examinee835
1.00 TEST0001
1 Examinee836
1.00 TEST0001
1 Examinee837
1.00 TEST0001
1 Examinee838
1.00 TEST0001
1 Examinee839
1.00 TEST0001
1 Examinee840
1.00 TEST0001
1 Examinee841
1.00 TEST0001
1 Examinee842
1.00 TEST0001
1 Examinee843
1.00 TEST0001
1 Examinee844
1.00 TEST0001
1 Examinee845
1.00 TEST0001
1 Examinee846
1.00 TEST0001
1 Examinee847
1.00 TEST0001
25
6
25
5
25
6
25
5
25
3
25
7
25
5
25
8
25
10
25
11
25
5
25
4
25
8
25
5
25
5
25
9
25
17
25
17
25
15
25
13
|
24.00 |
|
20.00 |
|
24.00 |
|
20.00 |
|
12.00 |
|
28.00 |
|
20.00 |
|
32.00 |
|
40.00 |
|
44.00 |
|
20.00 |
|
16.00 |
|
32.00 |
|
20.00 |
|
20.00 |
|
36.00 |
|
68.00 |
|
68.00 |
|
60.00 |
|
52.00 |
|
-2.1131 1.0661 |
|
-2.6776 1.1311 |
|
-2.1131 1.0661 |
|
-2.6776 1.1311 |
|
-4.0000 999.0000 |
|
-1.6043 1.0190 |
|
-2.6776 1.1311 |
|
-1.1343 0.9844 |
|
-0.2690 0.9410 |
|
0.1408 0.9291 |
|
-2.6776 1.1311 |
|
-3.3255 1.2245 |
|
-1.1343 0.9844 |
|
-2.6776 1.1311 |
|
-2.6776 1.1311 |
|
-0.6919 0.9590 |
|
2.5950 0.9729 |
|
2.5950 0.9729 |
|
1.7458 0.9345 |
|
0.9411 0.9213 |
260
1 Examinee848
1.00 TEST0001
1 Examinee849
1.00 TEST0001
1 Examinee850
1.00 TEST0001
1 Examinee851
1.00 TEST0001
1 Examinee852
1.00 TEST0001
1 Examinee853
1.00 TEST0001
1 Examinee854
1.00 TEST0001
1 Examinee855
1.00 TEST0001
1 Examinee856
1.00 TEST0001
1 Examinee857
1.00 TEST0001
1 Examinee858
1.00 TEST0001
1 Examinee859
1.00 TEST0001
1 Examinee860
1.00 TEST0001
1 Examinee861
1.00 TEST0001
1 Examinee862
1.00 TEST0001
1 Examinee863
1.00 TEST0001
1 Examinee864
1.00 TEST0001
1 Examinee865
1.00 TEST0001
1 Examinee866
1.00 TEST0001
1 Examinee867
1.00 TEST0001
25
12
25
8
25
14
25
10
25
13
25
16
25
11
25
13
25
11
25
13
25
17
25
12
25
10
25
7
25
12
25
8
25
10
25
14
25
8
25
3
|
48.00 |
|
32.00 |
|
56.00 |
|
40.00 |
|
52.00 |
|
64.00 |
|
44.00 |
|
52.00 |
|
44.00 |
|
52.00 |
|
68.00 |
|
48.00 |
|
40.00 |
|
28.00 |
|
48.00 |
|
32.00 |
|
40.00 |
|
56.00 |
|
32.00 |
|
12.00 |
|
0.5426 0.9226 |
|
-1.1343 0.9844 |
|
1.3406 0.9252 |
|
-0.2690 0.9410 |
|
0.9411 0.9213 |
|
2.1619 0.9500 |
|
0.1408 0.9291 |
|
0.9411 0.9213 |
|
0.1408 0.9291 |
|
0.9411 0.9213 |
|
2.5950 0.9729 |
|
0.5426 0.9226 |
|
-0.2690 0.9410 |
|
-1.6043 1.0190 |
|
0.5426 0.9226 |
|
-1.1343 0.9844 |
|
-0.2690 0.9410 |
|
1.3406 0.9252 |
|
-1.1343 0.9844 |
|
-4.0000 999.0000 |
261
1 Examinee868
1.00 TEST0001
1 Examinee869
1.00 TEST0001
1 Examinee870
1.00 TEST0001
1 Examinee871
1.00 TEST0001
1 Examinee872
1.00 TEST0001
1 Examinee873
1.00 TEST0001
1 Examinee874
1.00 TEST0001
1 Examinee875
1.00 TEST0001
1 Examinee876
1.00 TEST0001
1 Examinee877
1.00 TEST0001
1 Examinee878
1.00 TEST0001
1 Examinee879
1.00 TEST0001
1 Examinee880
1.00 TEST0001
1 Examinee881
1.00 TEST0001
1 Examinee882
1.00 TEST0001
1 Examinee883
1.00 TEST0001
1 Examinee884
1.00 TEST0001
1 Examinee885
1.00 TEST0001
1 Examinee886
1.00 TEST0001
1 Examinee887
1.00 TEST0001
25
5
25
5
25
15
25
10
25
6
25
10
25
9
25
13
25
9
25
10
25
5
25
13
25
10
25
7
25
5
25
14
25
11
25
9
25
11
25
9
|
20.00 |
|
20.00 |
|
60.00 |
|
40.00 |
|
24.00 |
|
40.00 |
|
36.00 |
|
52.00 |
|
36.00 |
|
40.00 |
|
20.00 |
|
52.00 |
|
40.00 |
|
28.00 |
|
20.00 |
|
56.00 |
|
44.00 |
|
36.00 |
|
44.00 |
|
36.00 |
|
-2.6776
|
-2.6776
|
1.7458
|
-0.2690
|
-2.1131
|
-0.2690
|
-0.6919
|
0.9411
|
-0.6919
|
-0.2690
|
-2.6776
|
0.9411
|
-0.2690
|
-1.6043
|
-2.6776
|
1.3406
|
0.1408
|
-0.6919
|
0.1408
|
-0.6919
1.1311 |
1.1311 |
0.9345 |
0.9410 |
1.0661 |
0.9410 |
0.9590 |
0.9213 |
0.9590 |
0.9410 |
1.1311 |
0.9213 |
0.9410 |
1.0190 |
1.1311 |
0.9252 |
0.9291 |
0.9590 |
0.9291 |
0.9590 |
262
1 Examinee888
1.00 TEST0001
1 Examinee889
1.00 TEST0001
1 Examinee890
1.00 TEST0001
1 Examinee891
1.00 TEST0001
1 Examinee892
1.00 TEST0001
1 Examinee893
1.00 TEST0001
1 Examinee894
1.00 TEST0001
1 Examinee895
1.00 TEST0001
1 Examinee896
1.00 TEST0001
1 Examinee897
1.00 TEST0001
1 Examinee898
1.00 TEST0001
1 Examinee899
1.00 TEST0001
1 Examinee900
1.00 TEST0001
1 Examinee901
1.00 TEST0001
1 Examinee902
1.00 TEST0001
1 Examinee903
1.00 TEST0001
1 Examinee904
1.00 TEST0001
1 Examinee905
1.00 TEST0001
1 Examinee906
1.00 TEST0001
1 Examinee907
1.00 TEST0001
25
7
25
10
25
13
25
14
25
7
25
13
25
10
25
12
25
9
25
14
25
13
25
11
25
7
25
8
25
3
25
8
25
13
25
10
25
11
25
10
|
28.00 |
|
40.00 |
|
52.00 |
|
56.00 |
|
28.00 |
|
52.00 |
|
40.00 |
|
48.00 |
|
36.00 |
|
56.00 |
|
52.00 |
|
44.00 |
|
28.00 |
|
32.00 |
|
12.00 |
|
32.00 |
|
52.00 |
|
40.00 |
|
44.00 |
|
40.00 |
|
-1.6043 1.0190 |
|
-0.2690 0.9410 |
|
0.9411 0.9213 |
|
1.3406 0.9252 |
|
-1.6043 1.0190 |
|
0.9411 0.9213 |
|
-0.2690 0.9410 |
|
0.5426 0.9226 |
|
-0.6919 0.9590 |
|
1.3406 0.9252 |
|
0.9411 0.9213 |
|
0.1408 0.9291 |
|
-1.6043 1.0190 |
|
-1.1343 0.9844 |
|
-4.0000 999.0000 |
|
-1.1343 0.9844 |
|
0.9411 0.9213 |
|
-0.2690 0.9410 |
|
0.1408 0.9291 |
|
-0.2690 0.9410 |
263
1 Examinee908
1.00 TEST0001
1 Examinee909
1.00 TEST0001
1 Examinee910
1.00 TEST0001
1 Examinee911
1.00 TEST0001
1 Examinee912
1.00 TEST0001
1 Examinee913
1.00 TEST0001
1 Examinee914
1.00 TEST0001
1 Examinee915
1.00 TEST0001
1 Examinee916
1.00 TEST0001
1 Examinee917
1.00 TEST0001
1 Examinee918
1.00 TEST0001
1 Examinee919
1.00 TEST0001
1 Examinee920
1.00 TEST0001
1 Examinee921
1.00 TEST0001
1 Examinee922
1.00 TEST0001
1 Examinee923
1.00 TEST0001
1 Examinee924
1.00 TEST0001
1 Examinee925
1.00 TEST0001
1 Examinee926
1.00 TEST0001
1 Examinee927
1.00 TEST0001
25
13
25
14
25
10
25
13
25
15
25
16
25
11
25
13
25
13
25
3
25
7
25
11
25
13
25
6
25
9
25
8
25
6
25
15
25
15
25
10
|
52.00 |
|
56.00 |
|
40.00 |
|
52.00 |
|
60.00 |
|
64.00 |
|
44.00 |
|
52.00 |
|
52.00 |
|
12.00 |
|
28.00 |
|
44.00 |
|
52.00 |
|
24.00 |
|
36.00 |
|
32.00 |
|
24.00 |
|
60.00 |
|
60.00 |
|
40.00 |
|
0.9411 0.9213 |
|
1.3406 0.9252 |
|
-0.2690 0.9410 |
|
0.9411 0.9213 |
|
1.7458 0.9345 |
|
2.1619 0.9500 |
|
0.1408 0.9291 |
|
0.9411 0.9213 |
|
0.9411 0.9213 |
|
-4.0000 999.0000 |
|
-1.6043 1.0190 |
|
0.1408 0.9291 |
|
0.9411 0.9213 |
|
-2.1131 1.0661 |
|
-0.6919 0.9590 |
|
-1.1343 0.9844 |
|
-2.1131 1.0661 |
|
1.7458 0.9345 |
|
1.7458 0.9345 |
|
-0.2690 0.9410 |
264
1 Examinee928
1.00 TEST0001
1 Examinee929
1.00 TEST0001
1 Examinee930
1.00 TEST0001
1 Examinee931
1.00 TEST0001
1 Examinee932
1.00 TEST0001
1 Examinee933
1.00 TEST0001
1 Examinee934
1.00 TEST0001
1 Examinee935
1.00 TEST0001
1 Examinee936
1.00 TEST0001
1 Examinee937
1.00 TEST0001
1 Examinee938
1.00 TEST0001
1 Examinee939
1.00 TEST0001
1 Examinee940
1.00 TEST0001
1 Examinee941
1.00 TEST0001
1 Examinee942
1.00 TEST0001
1 Examinee943
1.00 TEST0001
1 Examinee944
1.00 TEST0001
1 Examinee945
1.00 TEST0001
1 Examinee946
1.00 TEST0001
1 Examinee947
1.00 TEST0001
25
8
25
9
25
6
25
9
25
17
25
13
25
9
25
12
25
12
25
11
25
8
25
10
25
7
25
16
25
13
25
15
25
12
25
9
25
11
25
15
|
32.00 |
|
36.00 |
|
24.00 |
|
36.00 |
|
68.00 |
|
52.00 |
|
36.00 |
|
48.00 |
|
48.00 |
|
44.00 |
|
32.00 |
|
40.00 |
|
28.00 |
|
64.00 |
|
52.00 |
|
60.00 |
|
48.00 |
|
36.00 |
|
44.00 |
|
60.00 |
|
-1.1343
|
-0.6919
|
-2.1131
|
-0.6919
|
2.5950
|
0.9411
|
-0.6919
|
0.5426
|
0.5426
|
0.1408
|
-1.1343
|
-0.2690
|
-1.6043
|
2.1619
|
0.9411
|
1.7458
|
0.5426
|
-0.6919
|
0.1408
|
1.7458
0.9844 |
0.9590 |
1.0661 |
0.9590 |
0.9729 |
0.9213 |
0.9590 |
0.9226 |
0.9226 |
0.9291 |
0.9844 |
0.9410 |
1.0190 |
0.9500 |
0.9213 |
0.9345 |
0.9226 |
0.9590 |
0.9291 |
0.9345 |
265
1 Examinee948
1.00 TEST0001
1 Examinee949
1.00 TEST0001
1 Examinee950
1.00 TEST0001
1 Examinee951
1.00 TEST0001
1 Examinee952
1.00 TEST0001
1 Examinee953
1.00 TEST0001
1 Examinee954
1.00 TEST0001
1 Examinee955
1.00 TEST0001
1 Examinee956
1.00 TEST0001
1 Examinee957
1.00 TEST0001
1 Examinee958
1.00 TEST0001
1 Examinee959
1.00 TEST0001
1 Examinee960
1.00 TEST0001
1 Examinee961
1.00 TEST0001
1 Examinee962
1.00 TEST0001
1 Examinee963
1.00 TEST0001
1 Examinee964
1.00 TEST0001
1 Examinee965
1.00 TEST0001
1 Examinee966
1.00 TEST0001
1 Examinee967
1.00 TEST0001
25
12
25
4
25
14
25
8
25
14
25
14
25
13
25
10
25
12
25
13
25
6
25
9
25
6
25
8
25
16
25
7
25
6
25
12
25
13
25
13
|
48.00 |
|
16.00 |
|
56.00 |
|
32.00 |
|
56.00 |
|
56.00 |
|
52.00 |
|
40.00 |
|
48.00 |
|
52.00 |
|
24.00 |
|
36.00 |
|
24.00 |
|
32.00 |
|
64.00 |
|
28.00 |
|
24.00 |
|
48.00 |
|
52.00 |
|
52.00 |
|
0.5426
|
-3.3255
|
1.3406
|
-1.1343
|
1.3406
|
1.3406
|
0.9411
|
-0.2690
|
0.5426
|
0.9411
|
-2.1131
|
-0.6919
|
-2.1131
|
-1.1343
|
2.1619
|
-1.6043
|
-2.1131
|
0.5426
|
0.9411
|
0.9411
0.9226 |
1.2245 |
0.9252 |
0.9844 |
0.9252 |
0.9252 |
0.9213 |
0.9410 |
0.9226 |
0.9213 |
1.0661 |
0.9590 |
1.0661 |
0.9844 |
0.9500 |
1.0190 |
1.0661 |
0.9226 |
0.9213 |
0.9213 |
266
1 Examinee968
1.00 TEST0001
1 Examinee969
1.00 TEST0001
1 Examinee970
1.00 TEST0001
1 Examinee971
1.00 TEST0001
1 Examinee972
1.00 TEST0001
1 Examinee973
1.00 TEST0001
1 Examinee974
1.00 TEST0001
1 Examinee975
1.00 TEST0001
1 Examinee976
1.00 TEST0001
1 Examinee977
1.00 TEST0001
1 Examinee978
1.00 TEST0001
1 Examinee979
1.00 TEST0001
1 Examinee980
1.00 TEST0001
1 Examinee981
1.00 TEST0001
1 Examinee982
1.00 TEST0001
1 Examinee983
1.00 TEST0001
1 Examinee984
1.00 TEST0001
1 Examinee985
1.00 TEST0001
1 Examinee986
1.00 TEST0001
1 Examinee987
1.00 TEST0001
25
10
25
12
25
13
25
10
25
10
25
10
25
10
25
10
25
9
25
10
25
11
25
11
25
10
25
9
25
9
25
10
25
8
25
11
25
14
25
10
|
40.00 |
|
48.00 |
|
52.00 |
|
40.00 |
|
40.00 |
|
40.00 |
|
40.00 |
|
40.00 |
|
36.00 |
|
40.00 |
|
44.00 |
|
44.00 |
|
40.00 |
|
36.00 |
|
36.00 |
|
40.00 |
|
32.00 |
|
44.00 |
|
56.00 |
|
40.00 |
|
-0.2690
|
0.5426
|
0.9411
|
-0.2690
|
-0.2690
|
-0.2690
|
-0.2690
|
-0.2690
|
-0.6919
|
-0.2690
|
0.1408
|
0.1408
|
-0.2690
|
-0.6919
|
-0.6919
|
-0.2690
|
-1.1343
|
0.1408
|
1.3406
|
-0.2690
0.9410 |
0.9226 |
0.9213 |
0.9410 |
0.9410 |
0.9410 |
0.9410 |
0.9410 |
0.9590 |
0.9410 |
0.9291 |
0.9291 |
0.9410 |
0.9590 |
0.9590 |
0.9410 |
0.9844 |
0.9291 |
0.9252 |
0.9410 |
267
1 Examinee988
|
|
1.00 TEST0001 25 13 52.00 | 0.9411 0.9213 |
1 Examinee989
|
|
1.00 TEST0001 25 12 48.00 | 0.5426 0.9226 |
1 Examinee990
|
|
1.00 TEST0001 25
8 32.00 | -1.1343 0.9844 |
1 Examinee991
|
|
1.00 TEST0001 25 16 64.00 | 2.1619 0.9500 |
1 Examinee992
|
|
1.00 TEST0001 25 13 52.00 | 0.9411 0.9213 |
1 Examinee993
|
|
1.00 TEST0001 25
7 28.00 | -1.6043 1.0190 |
1 Examinee994
|
|
1.00 TEST0001 25 14 56.00 | 1.3406 0.9252 |
1 Examinee995
|
|
1.00 TEST0001 25 14 56.00 | 1.3406 0.9252 |
1 Examinee996
|
|
1.00 TEST0001 25 14 56.00 | 1.3406 0.9252 |
1 Examinee997
|
|
1.00 TEST0001 25 12 48.00 | 0.5426 0.9226 |
1 Examinee998
|
|
1.00 TEST0001 25
9 36.00 | -0.6919 0.9590 |
1 Examinee999
|
|
1.00 TEST0001 25 16 64.00 | 2.1619 0.9500 |
----------------------------------------------------------------
======================================
TEST0001
TEST0001
1.0000
268
TEST:
TEST0001
MEAN:
0.0306
S.D.:
1.3238
VARIANCE:
1.7523
HARMONIC ROOT-MEAN-SQUARE STANDARD ERRORS OF THE ML
ESTIMATES
TEST:
TEST0001
RMS:
0.9569
VARIANCE:
0.9157
EMPIRICAL
RELIABILITY:
0.4775
IN PHASE-3
IN PHASE-3
PH1
1
BILOG-MG V3.0
REV 19990104.1300
MODEL
DISTRIBUTED BY
269
CHICAGO, IL 60646
(800) 247-6113
(847) 675-0720
1
*** PHASE 1 ***
25 by 1000
---> FIND WARNING: 2 RECORDS NOT CONTAINING > IN COLUMN 1 HAVE
BEEN SKIPPED
NPArm = 2,
LOGistic,
SAVe;
===============================
270
CF.DAT
IF.DAT
CASE WEIGHTING
SF.DAT
NONE EMPLOYED
ITEM RESPONSE MODEL
>SAVE MASter = 'RG1.MAS',
CALib = 'RG1.CAL',
PARm = 'RG1.PAR',
SCOre = 'RG1.SCO',
COVariance = 'RG1.COV',
TSTat = 'RG1.TST',
ISTat = 'RG1.IST';
BILOG-MG SAVE FILES
[OUTPUT FILES]
BILOG-MG MASTER BINARY DATA RG1.MAS
271
CALIBRATION BINARY DATA FILERG1.CAL
CLASSICAL ITEM STATISTICS RG1.IST
RG1.PAR
RG1.SCO
ESTIMATED COVARIANCE FILE RG1.COV
RG1.TST
==========================
MAIN TEST LENGTHS:
25
>INPUT NTOtal = 25,
NALt = 3,
NIDchar = 11;
=========================
272
1
25
3
11
NUMBER OF GROUPS
1
1
TYPE OF DATA
>ITEMS ;
TEST SPECIFICATIONS
===================
INUmber = (1(1)25);
NUMBER OF ITEMS: 25
ITEM ITEM
ITEM ITEM
ITEM ITEM
ITEM ITEM
NUMBER NAME
NUMBER
NAME
----------------------------------------------------------------------1 ITEM0001
9 ITEM0009
17 ITEM0017 25 ITEM0025
2 ITEM0002 10 ITEM0010 18 ITEM0018
3 ITEM0003 11 ITEM0011 19 ITEM0019
4 ITEM0004 12 ITEM0012 20 ITEM0020
273
5 ITEM0005 13 ITEM0013 21 ITEM0021
6 ITEM0006 14 ITEM0014 22 ITEM0022
7 ITEM0007 15 ITEM0015 23 ITEM0023
8 ITEM0008 16 ITEM0016 24 ITEM0024
-----------------------------------------------------------------------
FORM SPECIFICATIONS
===================
(11A1, 25A1)
OBSERVATION #
1 WEIGHT:
GROUP #: 1
TRIED RIGHT
25.000 7.000
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 0.0 0.0 1.0 1.0 0.0 1.0 1.0 1.0 0.0 0.0
274
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0
ITEM 21 22 23 24 25
TRIED 1.0 1.0 1.0 1.0 1.0
RIGHT 0.0 0.0 0.0 0.0 0.0
OBSERVATION #
2 WEIGHT:
GROUP #: 1
TRIED RIGHT
25.000 11.000
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 0.0 1.0 1.0 0.0 1.0 1.0 0.0 1.0
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
ITEM 21 22 23 24 25
TRIED 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 0.0 0.0 1.0
999 OBSERVATIONS WRITTEN TO FILE: RG1.MAS
275
ITEM NAME
#TRIED #RIGHT PCT
------------------------------------------------------------------------1 ITEM0001 999.0 694.0 69.5 -0.82 0.246 0.324
2 ITEM0002 999.0 477.0 47.7 0.09 0.155 0.194
3 ITEM0003 999.0 579.0 58.0 -0.32 0.237 0.300
4 ITEM0004 999.0 571.0 57.2 -0.29 0.218 0.275
5 ITEM0005 999.0 461.0 46.1 0.15 0.159 0.199
6 ITEM0006 999.0 801.0 80.2 -1.40 0.266 0.380
7 ITEM0007 999.0 516.0 51.7 -0.07 0.236 0.295
8 ITEM0008 999.0 703.0 70.4 -0.86 0.219 0.289
9 ITEM0009 999.0 390.0 39.0 0.45 0.225 0.286
10 ITEM0010 999.0 560.0 56.1 -0.24 0.268 0.338
11 ITEM0011 999.0 264.0 26.4 1.02 0.022 0.030
12 ITEM0012 999.0 511.0 51.2 -0.05 0.256 0.321
13 ITEM0013 999.0 500.0 50.1 0.00 0.092 0.115
14 ITEM0014 999.0 743.0 74.4 -1.07 0.200 0.271
15 ITEM0015 999.0 195.0 19.5 1.42 0.091 0.130
16 ITEM0016 999.0 210.0 21.0 1.32 0.071 0.100
17 ITEM0017 999.0 281.0 28.1 0.94 0.047 0.062
18 ITEM0018 999.0 401.0 40.1 0.40 0.101 0.129
19 ITEM0019 999.0 284.0 28.4 0.92 0.128 0.170
20 ITEM0020 999.0 271.0 27.1 0.99 0.031 0.042
21 ITEM0021 999.0 290.0 29.0 0.89 0.108 0.144
22 ITEM0022 999.0 374.0 37.4 0.51 0.173 0.221
23 ITEM0023 999.0 198.0 19.8 1.40 0.043 0.061
24 ITEM0024 999.0 251.0 25.1 1.09 0.068 0.093
25 ITEM0025 999.0 187.0 18.7 1.47 0.069 0.100
-------------------------------------------------------------------------
IN PHASE-1
276
IN PHASE-1
11/29/2011 14:59:59
PH2
1
BILOG-MG V3.0
REV 19990329.1300
MODEL
*** PHASE 2 ***
25 by 1000
TPRior,
FLOat;
======================
277
20
0.0100
1.0000
2
NO
DATA HANDLING:
YES
PROGRAM DEFAULTS
1
--------------------------------------------------------------------------------
******************************
TEST0001
******************************
METHOD OF SOLUTION:
278
1
2
3
4
5
POINT -0.4000E+01 -0.3429E+01 -0.2857E+01 -0.2286E+01 -0.1714E+01
WEIGHT 0.7648E-04 0.6387E-03 0.3848E-02 0.1673E-01 0.5245E-01
6
7
8
9
10
POINT -0.1143E+01 -0.5714E+00 -0.8882E-15 0.5714E+00 0.1143E+01
WEIGHT 0.1186E+00 0.1936E+00 0.2280E+00 0.1936E+00 0.1186E+00
11
12
13
14
15
POINT 0.1714E+01 0.2286E+01 0.2857E+01 0.3429E+01 0.4000E+01
WEIGHT 0.5245E-01 0.1673E-01 0.3848E-02 0.6387E-03 0.7648E-04
THRESHOLDS
SLOPES
ASYMPTOTES
ITEM
BETA
---------------------------------------------------------------------ITEM0001 0.000 2.000 1.000 1.649
ITEM0002 0.000 2.000 1.000 1.649
ITEM0003 0.000 2.000 1.000 1.649
ITEM0004 0.000 2.000 1.000 1.649
ITEM0005 0.000 2.000 1.000 1.649
ITEM0006 0.000 2.000 1.000 1.649
ITEM0007 0.000 2.000 1.000 1.649
ITEM0008 0.000 2.000 1.000 1.649
ITEM0009 0.000 2.000 1.000 1.649
ITEM0010 0.000 2.000 1.000 1.649
ITEM0011 0.000 2.000 1.000 1.649
ITEM0012 0.000 2.000 1.000 1.649
ITEM0013 0.000 2.000 1.000 1.649
ITEM0014 0.000 2.000 1.000 1.649
ITEM0015 0.000 2.000 1.000 1.649
ITEM0016 0.000 2.000 1.000 1.649
ITEM0017 0.000 2.000 1.000 1.649
ITEM0018 0.000 2.000 1.000 1.649
279
ITEM0019 0.000 2.000 1.000 1.649
ITEM0020 0.000 2.000 1.000 1.649
ITEM0021 0.000 2.000 1.000 1.649
ITEM0022 0.000 2.000 1.000 1.649
ITEM0023 0.000 2.000 1.000 1.649
ITEM0024 0.000 2.000 1.000 1.649
ITEM0025 0.000 2.000 1.000 1.649
----------------------------------------------------------------------
[E-M CYCLES]
-2 LOG LIKELIHOOD =
CYCLE
30101.534
-2 LOG LIKELIHOOD =
30058.360
UPDATED PRIOR ON LOG SLOPES; MEAN & SD =
CYCLE
-2 LOG LIKELIHOOD =
30024.150
CYCLE
-0.89236 0.50000
1.56309 2.00000
-0.88145 0.50000
1.77732 2.00000
280
-2 LOG LIKELIHOOD =
30016.841
CYCLE
-2 LOG LIKELIHOOD =
30010.186
CYCLE
30009.910
-0.86727 0.50000
1.89405 2.00000
-2 LOG LIKELIHOOD =
30009.651
CYCLE
-0.86812 0.50000
1.89702 2.00000
-2 LOG LIKELIHOOD =
CYCLE
-0.87683 0.50000
1.83852 2.00000
-0.87111 0.50000
1.90345 2.00000
281
-2 LOG LIKELIHOOD =
30009.455
CYCLE
-0.87153 0.50000
1.90696 2.00000
[NEWTON CYCLES]
-2 LOG LIKELIHOOD:
CYCLE
-0.87274 0.50000
1.90914 2.00000
30009.4514
---------------------------------------------------------------------------27. 42. 62. 144. 200. 229. 155. 99. 41.
----------------------------------------------------------------------------2.487 -1.935 -1.325 -0.762 -0.263 0.261 0.794 1.302 1.975
---------------------------------------------------------------------------1
282
ITEM
CHISQ
DF
S.E.
S.E.
S.E.
S.E.
S.E. (PROB)
------------------------------------------------------------------------------ITEM0001 | 0.919 | 0.757 | -1.214 | 0.604 | 0.000 | 25.3 8.0
| 0.079* | 0.113* | 0.176* | 0.090* | 0.000* | (0.0014)
|
|
|
|
|
|
ITEM0002 | -0.099 | 0.462 | 0.214 | 0.420 | 0.000 | 18.1 9.0
| 0.065* | 0.084* | 0.146* | 0.076* | 0.000* | (0.0343)
|
|
|
|
|
|
ITEM0003 | 0.351 | 0.691 | -0.508 | 0.569 | 0.000 | 14.2 9.0
| 0.069* | 0.100* | 0.118* | 0.082* | 0.000* | (0.1163)
|
|
|
|
|
|
ITEM0004 | 0.312 | 0.653 | -0.478 | 0.547 | 0.000 | 18.5 9.0
| 0.069* | 0.096* | 0.119* | 0.080* | 0.000* | (0.0296)
|
|
|
|
|
|
ITEM0005 | -0.164 | 0.392 | 0.419 | 0.365 | 0.000 | 16.7 9.0
| 0.065* | 0.078* | 0.184* | 0.072* | 0.000* | (0.0533)
|
|
|
|
|
|
ITEM0006 | 1.821 | 1.306 | -1.394 | 0.794 | 0.000 | 26.8 7.0
| 0.123* | 0.159* | 0.132* | 0.096* | 0.000* | (0.0004)
|
|
|
|
|
|
ITEM0007 | 0.073 | 0.877 | -0.083 | 0.659 | 0.000 | 21.9 8.0
| 0.071* | 0.113* | 0.082* | 0.085* | 0.000* | (0.0051)
|
|
|
|
|
|
ITEM0008 | 1.024 | 0.959 | -1.067 | 0.692 | 0.000 | 24.2 7.0
| 0.085* | 0.125* | 0.133* | 0.090* | 0.000* | (0.0010)
|
|
|
|
|
|
ITEM0009 | -0.520 | 0.854 | 0.609 | 0.649 | 0.000 | 27.6 8.0
| 0.074* | 0.116* | 0.104* | 0.088* | 0.000* | (0.0006)
|
|
|
|
|
|
ITEM0010 | 0.275 | 0.822 | -0.335 | 0.635 | 0.000 | 19.9 9.0
| 0.071* | 0.108* | 0.093* | 0.084* | 0.000* | (0.0185)
|
|
|
|
|
|
ITEM0011 | -1.018 | 0.213 | 4.787 | 0.208 | 0.000 | 9.9 9.0
| 0.071* | 0.062* | 1.412* | 0.061* | 0.000* | (0.3582)
|
|
|
|
|
|
283
ITEM0012 | 0.049 | 0.822 | -0.059 | 0.635 | 0.000 | 24.6
| 0.070* | 0.114* | 0.086* | 0.088* | 0.000* | (0.0009)
|
|
|
|
|
|
ITEM0013 | -0.005 | 0.287 | 0.016 | 0.276 | 0.000 | 16.1
| 0.064* | 0.068* | 0.222* | 0.065* | 0.000* | (0.0643)
|
|
|
|
|
|
ITEM0014 | 1.150 | 0.631 | -1.821 | 0.534 | 0.000 | 8.6
| 0.081* | 0.101* | 0.277* | 0.085* | 0.000* | (0.3792)
|
|
|
|
|
|
ITEM0015 | -1.426 | 0.289 | 4.933 | 0.278 | 0.000 | 4.0
| 0.081* | 0.079* | 1.329* | 0.076* | 0.000* | (0.9098)
|
|
|
|
|
|
ITEM0016 | -1.315 | 0.230 | 5.713 | 0.224 | 0.000 | 1.5
| 0.077* | 0.068* | 1.683* | 0.066* | 0.000* | (0.9971)
|
|
|
|
|
|
ITEM0017 | -0.934 | 0.211 | 4.423 | 0.207 | 0.000 | 2.1
| 0.070* | 0.061* | 1.296* | 0.059* | 0.000* | (0.9898)
|
|
|
|
|
|
ITEM0018 | -0.408 | 0.257 | 1.584 | 0.249 | 0.000 | 3.1
| 0.065* | 0.066* | 0.465* | 0.064* | 0.000* | (0.9589)
|
|
|
|
|
|
ITEM0019 | -0.931 | 0.265 | 3.516 | 0.256 | 0.000 | 13.3
| 0.070* | 0.068* | 0.919* | 0.066* | 0.000* | (0.1515)
|
|
|
|
|
|
ITEM0020 | -0.969 | 0.173 | 5.606 | 0.170 | 0.000 | 21.5
| 0.070* | 0.052* | 1.711* | 0.051* | 0.000* | (0.0107)
|
|
|
|
|
|
ITEM0021 | -0.898 | 0.245 | 3.663 | 0.238 | 0.000 | 19.5
| 0.070* | 0.065* | 0.993* | 0.063* | 0.000* | (0.0209)
|
|
|
|
|
|
ITEM0022 | -0.535 | 0.395 | 1.352 | 0.368 | 0.000 | 10.0
| 0.067* | 0.082* | 0.313* | 0.077* | 0.000* | (0.3494)
|
|
|
|
|
|
ITEM0023 | -1.366 | 0.189 | 7.240 | 0.185 | 0.000 | 12.0
| 0.078* | 0.056* | 2.179* | 0.055* | 0.000* | (0.2139)
|
|
|
|
|
|
ITEM0024 | -1.087 | 0.222 | 4.906 | 0.216 | 0.000 | 6.0
| 0.072* | 0.062* | 1.402* | 0.061* | 0.000* | (0.7400)
|
|
|
|
|
|
ITEM0025 | -1.453 | 0.225 | 6.444 | 0.220 | 0.000 | 14.5
7.0
9.0
8.0
9.0
9.0
9.0
9.0
9.0
9.0
9.0
9.0
9.0
9.0
9.0
284
| 0.080* | 0.067* | 1.917* | 0.065* | 0.000* | (0.1065)
------------------------------------------------------------------------------* STANDARD ERROR
LARGEST CHANGE =
0.001596
379.9 215.0
(0.0000)
-------------------------------------------------------------------------------
PARAMETER
MEAN STN DEV
----------------------------------SLOPE
0.497 0.314
LOG(SLOPE) -0.888 0.627
1
2
3
4
5
POINT
-0.4057E+01 -0.3477E+01 -0.2898E+01 -0.2318E+01 -0.1738E+01
POSTERIOR 0.1128E-03 0.8939E-03 0.4912E-02 0.1853E-01 0.5066E-01
6
7
8
9
10
POINT
-0.1159E+01 -0.5794E+00 0.1756E-03 0.5797E+00 0.1159E+01
POSTERIOR 0.1116E+00 0.1928E+00 0.2347E+00 0.1970E+00 0.1173E+00
11
12
13
14
15
POINT
0.1739E+01 0.2318E+01 0.2898E+01 0.3478E+01 0.4057E+01
POSTERIOR 0.5060E-01 0.1614E-01 0.3902E-02 0.7258E-03 0.1023E-03
MEAN
S.D.
0.00000
1.00000
IN PHASE-2
285
IN PHASE-2
11/29/2011 15:00:00
PH3
1
BILOG-MG V3.0
MODEL
*** PHASE 3 ***
25 by 1000
>SCORE METhod = 1;
INFORMATION
MAXIMUM LIKELIHOOD
RG1.SCO
RG1.PH3
TYPE OF RESCALING:
NONE REQUESTED
286
----------------------1
NONE REQUESTED
NONE REQUESTED
******************************
SCORING
******************************
1
---------------------------------------------------------------1 Examinee001
|
|
1.00 TEST0001 25
7 28.00 | -0.9254 0.7237 |
1 Examinee002
|
|
1.00 TEST0001 25 11 44.00 | -0.5564 0.7277 |
1 Examinee003
|
|
1.00 TEST0001 25 11 44.00 | 0.4903 0.7999 |
1 Examinee004
|
|
1.00 TEST0001 25 12 48.00 | 0.2702 0.7780 |
1 Examinee005
|
|
1.00 TEST0001 25 10 40.00 | -0.0753 0.7508 |
1 Examinee006
|
|
1.00 TEST0001 25
9 36.00 | -0.0936 0.7496 |
1 Examinee007
|
|
1.00 TEST0001 25 10 40.00 | -0.2556 0.7400 |
1 Examinee008
|
|
1.00 TEST0001 25 11 44.00 | 0.1856 0.7706 |
1 Examinee009
|
|
1.00 TEST0001 25 14 56.00 | 1.0105 0.8655 |
1 Examinee010
|
|
1.00 TEST0001 25
9 36.00 | -0.1689 0.7449 |
1 Examinee011
|
|
1.00 TEST0001 25 12 48.00 | 0.1879 0.7708 |
S.E.
287
1 Examinee012
1.00 TEST0001
1 Examinee013
1.00 TEST0001
1 Examinee014
1.00 TEST0001
1 Examinee015
1.00 TEST0001
1 Examinee016
1.00 TEST0001
1 Examinee017
1.00 TEST0001
1 Examinee018
1.00 TEST0001
1 Examinee019
1.00 TEST0001
1 Examinee020
1.00 TEST0001
1 Examinee021
1.00 TEST0001
1 Examinee022
1.00 TEST0001
1 Examinee023
1.00 TEST0001
1 Examinee024
1.00 TEST0001
1 Examinee025
1.00 TEST0001
1 Examinee026
1.00 TEST0001
1 Examinee027
1.00 TEST0001
1 Examinee028
1.00 TEST0001
1 Examinee029
1.00 TEST0001
1 Examinee030
1.00 TEST0001
1 Examinee031
1.00 TEST0001
25
13
25
16
25
15
25
10
25
13
25
16
25
8
25
5
25
12
25
11
25
11
25
14
25
13
25
7
25
10
25
15
25
10
25
13
25
16
25
16
|
52.00 |
|
64.00 |
|
60.00 |
|
40.00 |
|
52.00 |
|
64.00 |
|
32.00 |
|
20.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
56.00 |
|
52.00 |
|
28.00 |
|
40.00 |
|
60.00 |
|
40.00 |
|
52.00 |
|
64.00 |
|
64.00 |
|
1.4873
|
1.7416
|
2.1319
|
0.3908
|
2.1557
|
1.3930
|
-0.8593
|
-2.2596
|
1.0448
|
0.3164
|
-0.0688
|
0.9554
|
0.5139
|
-0.8327
|
-0.0933
|
1.8563
|
-0.6170
|
1.0285
|
1.9520
|
2.4897
0.9438 |
0.9926 |
1.0765 |
0.7896 |
1.0819 |
0.9269 |
0.7234 |
0.8521 |
0.8706 |
0.7823 |
0.7512 |
0.8576 |
0.8024 |
0.7234 |
0.7496 |
1.0161 |
0.7261 |
0.8682 |
1.0365 |
1.1619 |
288
1 Examinee032
1.00 TEST0001
1 Examinee033
1.00 TEST0001
1 Examinee034
1.00 TEST0001
1 Examinee035
1.00 TEST0001
1 Examinee036
1.00 TEST0001
1 Examinee037
1.00 TEST0001
1 Examinee038
1.00 TEST0001
1 Examinee039
1.00 TEST0001
1 Examinee040
1.00 TEST0001
1 Examinee041
1.00 TEST0001
1 Examinee042
1.00 TEST0001
1 Examinee043
1.00 TEST0001
1 Examinee044
1.00 TEST0001
1 Examinee045
1.00 TEST0001
1 Examinee046
1.00 TEST0001
1 Examinee047
1.00 TEST0001
1 Examinee048
1.00 TEST0001
1 Examinee049
1.00 TEST0001
1 Examinee050
1.00 TEST0001
1 Examinee051
1.00 TEST0001
25
13
25
11
25
18
25
12
25
8
25
10
25
14
25
10
25
14
25
13
25
7
25
13
25
11
25
11
25
13
25
8
25
11
25
13
25
13
25
9
|
52.00 |
|
44.00 |
|
72.00 |
|
48.00 |
|
32.00 |
|
40.00 |
|
56.00 |
|
40.00 |
|
56.00 |
|
52.00 |
|
28.00 |
|
52.00 |
|
44.00 |
|
44.00 |
|
52.00 |
|
32.00 |
|
44.00 |
|
52.00 |
|
52.00 |
|
36.00 |
|
-0.1292
|
0.0896
|
4.0000
|
0.6408
|
-0.3980
|
-0.1817
|
1.2014
|
-0.5565
|
2.4761
|
1.8408
|
-1.6826
|
0.2842
|
0.4277
|
0.2619
|
1.5480
|
-1.4296
|
0.3986
|
1.5013
|
1.1887
|
-0.3747
0.7473 |
0.7627 |
999.0000 |
0.8168 |
0.7333 |
0.7441 |
0.8948 |
0.7277 |
1.1585 |
1.0129 |
0.7653 |
0.7793 |
0.7933 |
0.7773 |
0.9550 |
0.7429 |
0.7903 |
0.9463 |
0.8927 |
0.7343 |
289
1 Examinee052
1.00 TEST0001
1 Examinee053
1.00 TEST0001
1 Examinee054
1.00 TEST0001
1 Examinee055
1.00 TEST0001
1 Examinee056
1.00 TEST0001
1 Examinee057
1.00 TEST0001
1 Examinee058
1.00 TEST0001
1 Examinee059
1.00 TEST0001
1 Examinee060
1.00 TEST0001
1 Examinee061
1.00 TEST0001
1 Examinee062
1.00 TEST0001
1 Examinee063
1.00 TEST0001
1 Examinee064
1.00 TEST0001
1 Examinee065
1.00 TEST0001
1 Examinee066
1.00 TEST0001
1 Examinee067
1.00 TEST0001
1 Examinee068
1.00 TEST0001
1 Examinee069
1.00 TEST0001
1 Examinee070
1.00 TEST0001
1 Examinee071
1.00 TEST0001
25
13
25
11
25
9
25
8
25
13
25
16
25
16
25
8
25
10
25
11
25
8
25
13
25
12
25
11
25
13
25
13
25
13
25
9
25
15
25
11
|
52.00 |
|
44.00 |
|
36.00 |
|
32.00 |
|
52.00 |
|
64.00 |
|
64.00 |
|
32.00 |
|
40.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
48.00 |
|
44.00 |
|
52.00 |
|
52.00 |
|
52.00 |
|
36.00 |
|
60.00 |
|
44.00 |
|
0.0433
|
0.5966
|
-0.5767
|
-0.8013
|
1.0484
|
2.9740
|
2.2855
|
-1.1468
|
-0.8190
|
-0.2685
|
-0.9401
|
0.3628
|
0.4234
|
0.3433
|
0.2761
|
1.7975
|
0.7473
|
-1.0452
|
1.2995
|
-0.2360
0.7592 |
0.8117 |
0.7271 |
0.7235 |
0.8711 |
1.2876 |
1.1122 |
0.7282 |
0.7234 |
0.7393 |
0.7238 |
0.7868 |
0.7929 |
0.7849 |
0.7786 |
1.0039 |
0.8298 |
0.7254 |
0.9109 |
0.7411 |
290
1 Examinee072
1.00 TEST0001
1 Examinee073
1.00 TEST0001
1 Examinee074
1.00 TEST0001
1 Examinee075
1.00 TEST0001
1 Examinee076
1.00 TEST0001
1 Examinee077
1.00 TEST0001
1 Examinee078
1.00 TEST0001
1 Examinee079
1.00 TEST0001
1 Examinee080
1.00 TEST0001
1 Examinee081
1.00 TEST0001
1 Examinee082
1.00 TEST0001
1 Examinee083
1.00 TEST0001
1 Examinee084
1.00 TEST0001
1 Examinee085
1.00 TEST0001
1 Examinee086
1.00 TEST0001
1 Examinee087
1.00 TEST0001
1 Examinee088
1.00 TEST0001
1 Examinee089
1.00 TEST0001
1 Examinee090
1.00 TEST0001
1 Examinee091
1.00 TEST0001
25
16
25
13
25
13
25
16
25
18
25
15
25
7
25
14
25
17
25
16
25
8
25
11
25
10
25
11
25
14
25
13
25
11
25
10
25
13
25
12
|
64.00 |
|
52.00 |
|
52.00 |
|
64.00 |
|
72.00 |
|
60.00 |
|
28.00 |
|
56.00 |
|
68.00 |
|
64.00 |
|
32.00 |
|
44.00 |
|
40.00 |
|
44.00 |
|
56.00 |
|
52.00 |
|
44.00 |
|
40.00 |
|
52.00 |
|
48.00 |
|
1.8410
|
0.4547
|
-0.2520
|
1.6076
|
3.1138
|
0.8076
|
-1.4075
|
1.4728
|
3.8200
|
2.5881
|
-0.8707
|
-0.1028
|
-0.3389
|
-0.6603
|
0.5156
|
0.7176
|
-0.6547
|
-0.3918
|
1.7121
|
1.0458
1.0129 |
0.7961 |
0.7402 |
0.9663 |
1.3255 |
0.8375 |
0.7413 |
0.9411 |
1.5215 |
1.1866 |
0.7234 |
0.7490 |
0.7359 |
0.7252 |
0.8026 |
0.8261 |
0.7253 |
0.7335 |
0.9866 |
0.8707 |
291
1 Examinee092
1.00 TEST0001
1 Examinee093
1.00 TEST0001
1 Examinee094
1.00 TEST0001
1 Examinee095
1.00 TEST0001
1 Examinee096
1.00 TEST0001
1 Examinee097
1.00 TEST0001
1 Examinee098
1.00 TEST0001
1 Examinee099
1.00 TEST0001
1 Examinee100
1.00 TEST0001
1 Examinee101
1.00 TEST0001
1 Examinee102
1.00 TEST0001
1 Examinee103
1.00 TEST0001
1 Examinee104
1.00 TEST0001
1 Examinee105
1.00 TEST0001
1 Examinee106
1.00 TEST0001
1 Examinee107
1.00 TEST0001
1 Examinee108
1.00 TEST0001
1 Examinee109
1.00 TEST0001
1 Examinee110
1.00 TEST0001
1 Examinee111
1.00 TEST0001
25
10
25
13
25
8
25
13
25
11
25
17
25
12
25
18
25
11
25
9
25
10
25
11
25
15
25
11
25
14
25
11
25
8
25
7
25
10
25
12
|
40.00 |
|
52.00 |
|
32.00 |
|
52.00 |
|
44.00 |
|
68.00 |
|
48.00 |
|
72.00 |
|
44.00 |
|
36.00 |
|
40.00 |
|
44.00 |
|
60.00 |
|
44.00 |
|
56.00 |
|
44.00 |
|
32.00 |
|
28.00 |
|
40.00 |
|
48.00 |
|
-0.2423
|
0.5694
|
-0.5330
|
0.8922
|
0.0608
|
2.9270
|
0.8808
|
3.2052
|
0.7259
|
-0.6032
|
-0.4676
|
0.5936
|
1.3341
|
0.2473
|
0.4410
|
0.6447
|
-1.0053
|
-2.0888
|
0.0577
|
0.9138
0.7407 |
0.8085 |
0.7284 |
0.8488 |
0.7605 |
1.2750 |
0.8473 |
1.3505 |
0.8271 |
0.7265 |
0.7306 |
0.8113 |
0.9167 |
0.7760 |
0.7947 |
0.8173 |
0.7247 |
0.8212 |
0.7603 |
0.8518 |
292
1 Examinee112
1.00 TEST0001
1 Examinee113
1.00 TEST0001
1 Examinee114
1.00 TEST0001
1 Examinee115
1.00 TEST0001
1 Examinee116
1.00 TEST0001
1 Examinee117
1.00 TEST0001
1 Examinee118
1.00 TEST0001
1 Examinee119
1.00 TEST0001
1 Examinee120
1.00 TEST0001
1 Examinee121
1.00 TEST0001
1 Examinee122
1.00 TEST0001
1 Examinee123
1.00 TEST0001
1 Examinee124
1.00 TEST0001
1 Examinee125
1.00 TEST0001
1 Examinee126
1.00 TEST0001
1 Examinee127
1.00 TEST0001
1 Examinee128
1.00 TEST0001
1 Examinee129
1.00 TEST0001
1 Examinee130
1.00 TEST0001
1 Examinee131
1.00 TEST0001
25
12
25
10
25
7
25
9
25
13
25
9
25
15
25
10
25
9
25
8
25
7
25
8
25
11
25
11
25
12
25
14
25
11
25
6
25
5
25
9
|
48.00 |
|
40.00 |
|
28.00 |
|
36.00 |
|
52.00 |
|
36.00 |
|
60.00 |
|
40.00 |
|
36.00 |
|
32.00 |
|
28.00 |
|
32.00 |
|
44.00 |
|
44.00 |
|
48.00 |
|
56.00 |
|
44.00 |
|
24.00 |
|
20.00 |
|
36.00 |
|
0.6008
|
-0.1702
|
-0.8975
|
-0.8235
|
1.3945
|
-0.6497
|
1.7090
|
-0.4521
|
-0.7954
|
-1.0109
|
-1.7924
|
-0.1700
|
0.4274
|
0.4501
|
1.1383
|
1.9557
|
0.1478
|
-1.9028
|
-1.3811
|
-0.7593
0.8121 |
0.7448 |
0.7235 |
0.7234 |
0.9272 |
0.7254 |
0.9860 |
0.7311 |
0.7235 |
0.7248 |
0.7780 |
0.7448 |
0.7933 |
0.7956 |
0.8848 |
1.0373 |
0.7674 |
0.7925 |
0.7396 |
0.7238 |
293
1 Examinee132
1.00 TEST0001
1 Examinee133
1.00 TEST0001
1 Examinee134
1.00 TEST0001
1 Examinee135
1.00 TEST0001
1 Examinee136
1.00 TEST0001
1 Examinee137
1.00 TEST0001
1 Examinee138
1.00 TEST0001
1 Examinee139
1.00 TEST0001
1 Examinee140
1.00 TEST0001
1 Examinee141
1.00 TEST0001
1 Examinee142
1.00 TEST0001
1 Examinee143
1.00 TEST0001
1 Examinee144
1.00 TEST0001
1 Examinee145
1.00 TEST0001
1 Examinee146
1.00 TEST0001
1 Examinee147
1.00 TEST0001
1 Examinee148
1.00 TEST0001
1 Examinee149
1.00 TEST0001
1 Examinee150
1.00 TEST0001
1 Examinee151
1.00 TEST0001
25
14
25
12
25
4
25
9
25
10
25
10
25
14
25
7
25
8
25
17
25
8
25
7
25
10
25
12
25
8
25
10
25
8
25
7
25
12
25
12
|
56.00 |
|
48.00 |
|
16.00 |
|
36.00 |
|
40.00 |
|
40.00 |
|
56.00 |
|
28.00 |
|
32.00 |
|
68.00 |
|
32.00 |
|
28.00 |
|
40.00 |
|
48.00 |
|
32.00 |
|
40.00 |
|
32.00 |
|
28.00 |
|
48.00 |
|
48.00 |
|
0.5038
|
0.0622
|
-2.7116
|
-0.3425
|
0.1613
|
-0.3157
|
1.3165
|
-0.3294
|
-0.6807
|
2.8680
|
-0.9500
|
-0.4011
|
-0.3575
|
0.3513
|
-0.8814
|
-0.4245
|
-0.9695
|
-0.9603
|
1.3678
|
0.9364
0.8013 |
0.7606 |
0.9541 |
0.7357 |
0.7685 |
0.7370 |
0.9137 |
0.7363 |
0.7249 |
1.2593 |
0.7239 |
0.7331 |
0.7350 |
0.7857 |
0.7234 |
0.7322 |
0.7241 |
0.7240 |
0.9225 |
0.8549 |
294
1 Examinee152
1.00 TEST0001
1 Examinee153
1.00 TEST0001
1 Examinee154
1.00 TEST0001
1 Examinee155
1.00 TEST0001
1 Examinee156
1.00 TEST0001
1 Examinee157
1.00 TEST0001
1 Examinee158
1.00 TEST0001
1 Examinee159
1.00 TEST0001
1 Examinee160
1.00 TEST0001
1 Examinee161
1.00 TEST0001
1 Examinee162
1.00 TEST0001
1 Examinee163
1.00 TEST0001
1 Examinee164
1.00 TEST0001
1 Examinee165
1.00 TEST0001
1 Examinee166
1.00 TEST0001
1 Examinee167
1.00 TEST0001
1 Examinee168
1.00 TEST0001
1 Examinee169
1.00 TEST0001
1 Examinee170
1.00 TEST0001
1 Examinee171
1.00 TEST0001
25
11
25
16
25
16
25
10
25
10
25
16
25
15
25
19
25
16
25
17
25
5
25
10
25
17
25
7
25
12
25
8
25
13
25
16
25
9
25
7
|
44.00 |
|
64.00 |
|
64.00 |
|
40.00 |
|
40.00 |
|
64.00 |
|
60.00 |
|
76.00 |
|
64.00 |
|
68.00 |
|
20.00 |
|
40.00 |
|
68.00 |
|
28.00 |
|
48.00 |
|
32.00 |
|
52.00 |
|
64.00 |
|
36.00 |
|
28.00 |
|
0.1122
|
1.6951
|
2.4342
|
0.1276
|
-0.2875
|
2.0381
|
1.7038
|
3.8322
|
1.5176
|
2.0416
|
-2.6800
|
0.5538
|
1.6993
|
-0.8240
|
0.0224
|
-0.7830
|
0.8953
|
2.4467
|
-0.7981
|
-1.1765
0.7645 |
0.9833 |
1.1482 |
0.7658 |
0.7384 |
1.0554 |
0.9850 |
1.5249 |
0.9493 |
1.0561 |
0.9461 |
0.8068 |
0.9841 |
0.7234 |
0.7576 |
0.7236 |
0.8492 |
1.1512 |
0.7235 |
0.7293 |
295
1 Examinee172
1.00 TEST0001
1 Examinee173
1.00 TEST0001
1 Examinee174
1.00 TEST0001
1 Examinee175
1.00 TEST0001
1 Examinee176
1.00 TEST0001
1 Examinee177
1.00 TEST0001
1 Examinee178
1.00 TEST0001
1 Examinee179
1.00 TEST0001
1 Examinee180
1.00 TEST0001
1 Examinee181
1.00 TEST0001
1 Examinee182
1.00 TEST0001
1 Examinee183
1.00 TEST0001
1 Examinee184
1.00 TEST0001
1 Examinee185
1.00 TEST0001
1 Examinee186
1.00 TEST0001
1 Examinee187
1.00 TEST0001
1 Examinee188
1.00 TEST0001
1 Examinee189
1.00 TEST0001
1 Examinee190
1.00 TEST0001
1 Examinee191
1.00 TEST0001
25
14
25
10
25
17
25
17
25
14
25
8
25
12
25
9
25
11
25
13
25
13
25
9
25
12
25
9
25
11
25
10
25
12
25
12
25
8
25
11
|
56.00 |
|
40.00 |
|
68.00 |
|
68.00 |
|
56.00 |
|
32.00 |
|
48.00 |
|
36.00 |
|
44.00 |
|
52.00 |
|
52.00 |
|
36.00 |
|
48.00 |
|
36.00 |
|
44.00 |
|
40.00 |
|
48.00 |
|
48.00 |
|
32.00 |
|
44.00 |
|
1.6326
|
0.0973
|
1.6870
|
3.1206
|
0.9913
|
-0.5514
|
1.2772
|
-0.1607
|
-0.0619
|
0.1859
|
0.5326
|
-0.8687
|
0.2206
|
-1.2102
|
1.2694
|
0.4252
|
-0.0500
|
0.0315
|
-1.2793
|
-0.3199
0.9711 |
0.7633 |
0.9817 |
1.3273 |
0.8627 |
0.7278 |
0.9071 |
0.7454 |
0.7517 |
0.7706 |
0.8045 |
0.7234 |
0.7736 |
0.7306 |
0.9059 |
0.7930 |
0.7525 |
0.7583 |
0.7338 |
0.7368 |
296
1 Examinee192
1.00 TEST0001
1 Examinee193
1.00 TEST0001
1 Examinee194
1.00 TEST0001
1 Examinee195
1.00 TEST0001
1 Examinee196
1.00 TEST0001
1 Examinee197
1.00 TEST0001
1 Examinee198
1.00 TEST0001
1 Examinee199
1.00 TEST0001
1 Examinee200
1.00 TEST0001
1 Examinee201
1.00 TEST0001
1 Examinee202
1.00 TEST0001
1 Examinee203
1.00 TEST0001
1 Examinee204
1.00 TEST0001
1 Examinee205
1.00 TEST0001
1 Examinee206
1.00 TEST0001
1 Examinee207
1.00 TEST0001
1 Examinee208
1.00 TEST0001
1 Examinee209
1.00 TEST0001
1 Examinee210
1.00 TEST0001
1 Examinee211
1.00 TEST0001
25
8
25
12
25
12
25
15
25
20
25
13
25
15
25
10
25
11
25
12
25
14
25
16
25
12
25
11
25
11
25
9
25
11
25
12
25
12
25
10
|
32.00 |
|
48.00 |
|
48.00 |
|
60.00 |
|
80.00 |
|
52.00 |
|
60.00 |
|
40.00 |
|
44.00 |
|
48.00 |
|
56.00 |
|
64.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
36.00 |
|
44.00 |
|
48.00 |
|
48.00 |
|
40.00 |
|
-1.1321
|
0.5073
|
0.4849
|
1.9756
|
4.0000
|
2.0753
|
0.3939
|
-0.0016
|
1.2150
|
0.0092
|
0.7755
|
2.6572
|
-0.1965
|
0.5423
|
-0.2980
|
-0.9749
|
0.6613
|
0.6757
|
0.5505
|
-0.6202
0.7277 |
0.8017 |
0.7993 |
1.0416 |
999.0000 |
1.0637 |
0.7899 |
0.7559 |
0.8970 |
0.7567 |
0.8334 |
1.2042 |
0.7433 |
0.8055 |
0.7378 |
0.7242 |
0.8192 |
0.8210 |
0.8064 |
0.7261 |
297
1 Examinee212
1.00 TEST0001
1 Examinee213
1.00 TEST0001
1 Examinee214
1.00 TEST0001
1 Examinee215
1.00 TEST0001
1 Examinee216
1.00 TEST0001
1 Examinee217
1.00 TEST0001
1 Examinee218
1.00 TEST0001
1 Examinee219
1.00 TEST0001
1 Examinee220
1.00 TEST0001
1 Examinee221
1.00 TEST0001
1 Examinee222
1.00 TEST0001
1 Examinee223
1.00 TEST0001
1 Examinee224
1.00 TEST0001
1 Examinee225
1.00 TEST0001
1 Examinee226
1.00 TEST0001
1 Examinee227
1.00 TEST0001
1 Examinee228
1.00 TEST0001
1 Examinee229
1.00 TEST0001
1 Examinee230
1.00 TEST0001
1 Examinee231
1.00 TEST0001
25
7
25
7
25
8
25
15
25
12
25
17
25
15
25
17
25
8
25
22
25
14
25
12
25
16
25
16
25
19
25
20
25
11
25
9
25
13
25
10
|
28.00 |
|
28.00 |
|
32.00 |
|
60.00 |
|
48.00 |
|
68.00 |
|
60.00 |
|
68.00 |
|
32.00 |
|
88.00 |
|
56.00 |
|
48.00 |
|
64.00 |
|
64.00 |
|
76.00 |
|
80.00 |
|
44.00 |
|
36.00 |
|
52.00 |
|
40.00 |
|
-0.5640
|
-0.8048
|
-0.3699
|
1.2766
|
0.1940
|
2.2294
|
2.7071
|
3.3578
|
-0.1910
|
4.0000
|
2.4662
|
0.0244
|
2.5957
|
2.0978
|
3.3485
|
4.0000
|
0.5611
|
-0.7349
|
1.6029
|
0.1533
0.7275 |
0.7235 |
0.7345 |
0.9071 |
0.7713 |
1.0990 |
1.2171 |
1.3926 |
0.7436 |
999.0000 |
1.1561 |
0.7578 |
1.1885 |
1.0687 |
1.3900 |
999.0000 |
0.8076 |
0.7241 |
0.9654 |
0.7679 |
298
1 Examinee232
1.00 TEST0001
1 Examinee233
1.00 TEST0001
1 Examinee234
1.00 TEST0001
1 Examinee235
1.00 TEST0001
1 Examinee236
1.00 TEST0001
1 Examinee237
1.00 TEST0001
1 Examinee238
1.00 TEST0001
1 Examinee239
1.00 TEST0001
1 Examinee240
1.00 TEST0001
1 Examinee241
1.00 TEST0001
1 Examinee242
1.00 TEST0001
1 Examinee243
1.00 TEST0001
1 Examinee244
1.00 TEST0001
1 Examinee245
1.00 TEST0001
1 Examinee246
1.00 TEST0001
1 Examinee247
1.00 TEST0001
1 Examinee248
1.00 TEST0001
1 Examinee249
1.00 TEST0001
1 Examinee250
1.00 TEST0001
1 Examinee251
1.00 TEST0001
25
8
25
9
25
16
25
9
25
12
25
11
25
11
25
16
25
10
25
13
25
14
25
9
25
10
25
8
25
12
25
7
25
12
25
8
25
8
25
10
|
32.00 |
|
36.00 |
|
64.00 |
|
36.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
64.00 |
|
40.00 |
|
52.00 |
|
56.00 |
|
36.00 |
|
40.00 |
|
32.00 |
|
48.00 |
|
28.00 |
|
48.00 |
|
32.00 |
|
32.00 |
|
40.00 |
|
-0.8455
|
0.0827
|
1.8934
|
-0.4982
|
0.4260
|
-0.8964
|
1.5268
|
1.9829
|
0.5093
|
0.7330
|
1.0875
|
-0.5188
|
-0.7148
|
-0.4103
|
0.1502
|
-0.8308
|
0.1307
|
-0.7781
|
-0.1949
|
-0.4820
0.7234 |
0.7622 |
1.0240 |
0.7295 |
0.7931 |
0.7235 |
0.9510 |
1.0432 |
0.8019 |
0.8280 |
0.8770 |
0.7288 |
0.7243 |
0.7328 |
0.7676 |
0.7234 |
0.7660 |
0.7237 |
0.7434 |
0.7300 |
299
1 Examinee252
1.00 TEST0001
1 Examinee253
1.00 TEST0001
1 Examinee254
1.00 TEST0001
1 Examinee255
1.00 TEST0001
1 Examinee256
1.00 TEST0001
1 Examinee257
1.00 TEST0001
1 Examinee258
1.00 TEST0001
1 Examinee259
1.00 TEST0001
1 Examinee260
1.00 TEST0001
1 Examinee261
1.00 TEST0001
1 Examinee262
1.00 TEST0001
1 Examinee263
1.00 TEST0001
1 Examinee264
1.00 TEST0001
1 Examinee265
1.00 TEST0001
1 Examinee266
1.00 TEST0001
1 Examinee267
1.00 TEST0001
1 Examinee268
1.00 TEST0001
1 Examinee269
1.00 TEST0001
1 Examinee270
1.00 TEST0001
1 Examinee271
1.00 TEST0001
25
12
25
5
25
12
25
9
25
17
25
9
25
16
25
14
25
12
25
15
25
12
25
9
25
9
25
6
25
7
25
5
25
14
25
6
25
11
25
8
|
48.00 |
|
20.00 |
|
48.00 |
|
36.00 |
|
68.00 |
|
36.00 |
|
64.00 |
|
56.00 |
|
48.00 |
|
60.00 |
|
48.00 |
|
36.00 |
|
36.00 |
|
24.00 |
|
28.00 |
|
20.00 |
|
56.00 |
|
24.00 |
|
44.00 |
|
32.00 |
|
0.8746
|
-2.6247
|
0.4389
|
-0.7433
|
3.0433
|
-0.4791
|
3.2100
|
1.8406
|
0.4783
|
1.9427
|
0.8285
|
0.1851
|
-0.2531
|
-1.4407
|
-1.3410
|
-3.6422
|
2.3808
|
-0.8150
|
0.0238
|
-0.9328
0.8464 |
0.9323 |
0.7945 |
0.7240 |
1.3063 |
0.7301 |
1.3518 |
1.0128 |
0.7986 |
1.0345 |
0.8403 |
0.7705 |
0.7402 |
0.7437 |
0.7371 |
1.2477 |
1.1351 |
0.7235 |
0.7577 |
0.7237 |
300
1 Examinee272
1.00 TEST0001
1 Examinee273
1.00 TEST0001
1 Examinee274
1.00 TEST0001
1 Examinee275
1.00 TEST0001
1 Examinee276
1.00 TEST0001
1 Examinee277
1.00 TEST0001
1 Examinee278
1.00 TEST0001
1 Examinee279
1.00 TEST0001
1 Examinee280
1.00 TEST0001
1 Examinee281
1.00 TEST0001
1 Examinee282
1.00 TEST0001
1 Examinee283
1.00 TEST0001
1 Examinee284
1.00 TEST0001
1 Examinee285
1.00 TEST0001
1 Examinee286
1.00 TEST0001
1 Examinee287
1.00 TEST0001
1 Examinee288
1.00 TEST0001
1 Examinee289
1.00 TEST0001
1 Examinee290
1.00 TEST0001
1 Examinee291
1.00 TEST0001
25
7
25
9
25
14
25
13
25
13
25
12
25
10
25
11
25
13
25
9
25
13
25
13
25
10
25
10
25
9
25
14
25
11
25
10
25
12
25
8
|
28.00 |
|
36.00 |
|
56.00 |
|
52.00 |
|
52.00 |
|
48.00 |
|
40.00 |
|
44.00 |
|
52.00 |
|
36.00 |
|
52.00 |
|
52.00 |
|
40.00 |
|
40.00 |
|
36.00 |
|
56.00 |
|
44.00 |
|
40.00 |
|
48.00 |
|
32.00 |
|
-1.0512
|
0.0373
|
0.8249
|
0.3102
|
0.6762
|
0.6704
|
-0.6661
|
-0.9086
|
1.2492
|
0.3008
|
0.7402
|
0.7325
|
0.2639
|
-0.2871
|
-0.4322
|
1.6055
|
0.3305
|
0.3333
|
0.1877
|
-1.4659
0.7255 |
0.7587 |
0.8398 |
0.7818 |
0.8210 |
0.8203 |
0.7251 |
0.7236 |
0.9025 |
0.7809 |
0.8289 |
0.8279 |
0.7775 |
0.7384 |
0.7319 |
0.9659 |
0.7837 |
0.7839 |
0.7708 |
0.7455 |
301
1 Examinee292
1.00 TEST0001
1 Examinee293
1.00 TEST0001
1 Examinee294
1.00 TEST0001
1 Examinee295
1.00 TEST0001
1 Examinee296
1.00 TEST0001
1 Examinee297
1.00 TEST0001
1 Examinee298
1.00 TEST0001
1 Examinee299
1.00 TEST0001
1 Examinee300
1.00 TEST0001
1 Examinee301
1.00 TEST0001
1 Examinee302
1.00 TEST0001
1 Examinee303
1.00 TEST0001
1 Examinee304
1.00 TEST0001
1 Examinee305
1.00 TEST0001
1 Examinee306
1.00 TEST0001
1 Examinee307
1.00 TEST0001
1 Examinee308
1.00 TEST0001
1 Examinee309
1.00 TEST0001
1 Examinee310
1.00 TEST0001
1 Examinee311
1.00 TEST0001
25
12
25
9
25
10
25
13
25
13
25
10
25
13
25
10
25
9
25
13
25
10
25
5
25
10
25
14
25
6
25
13
25
12
25
14
25
14
25
9
|
48.00 |
|
36.00 |
|
40.00 |
|
52.00 |
|
52.00 |
|
40.00 |
|
52.00 |
|
40.00 |
|
36.00 |
|
52.00 |
|
40.00 |
|
20.00 |
|
40.00 |
|
56.00 |
|
24.00 |
|
52.00 |
|
48.00 |
|
56.00 |
|
56.00 |
|
36.00 |
|
0.5444
|
-1.0261
|
0.2578
|
-0.1282
|
0.1273
|
-0.0879
|
0.0916
|
0.1504
|
-0.6608
|
0.3192
|
0.0066
|
-1.5887
|
-0.6050
|
1.7245
|
-1.2900
|
0.5113
|
0.1338
|
0.3197
|
1.3058
|
-0.8002
0.8058 |
0.7250 |
0.7769 |
0.7474 |
0.7657 |
0.7500 |
0.7629 |
0.7676 |
0.7252 |
0.7826 |
0.7565 |
0.7559 |
0.7264 |
0.9891 |
0.7343 |
0.8021 |
0.7663 |
0.7826 |
0.9119 |
0.7235 |
302
1 Examinee312
1.00 TEST0001
1 Examinee313
1.00 TEST0001
1 Examinee314
1.00 TEST0001
1 Examinee315
1.00 TEST0001
1 Examinee316
1.00 TEST0001
1 Examinee317
1.00 TEST0001
1 Examinee318
1.00 TEST0001
1 Examinee319
1.00 TEST0001
1 Examinee320
1.00 TEST0001
1 Examinee321
1.00 TEST0001
1 Examinee322
1.00 TEST0001
1 Examinee323
1.00 TEST0001
1 Examinee324
1.00 TEST0001
1 Examinee325
1.00 TEST0001
1 Examinee326
1.00 TEST0001
1 Examinee327
1.00 TEST0001
1 Examinee328
1.00 TEST0001
1 Examinee329
1.00 TEST0001
1 Examinee330
1.00 TEST0001
1 Examinee331
1.00 TEST0001
25
9
25
5
25
7
25
4
25
7
25
15
25
11
25
8
25
8
25
8
25
19
25
15
25
12
25
12
25
11
25
8
25
12
25
12
25
14
25
14
|
36.00 |
|
20.00 |
|
28.00 |
|
16.00 |
|
28.00 |
|
60.00 |
|
44.00 |
|
32.00 |
|
32.00 |
|
32.00 |
|
76.00 |
|
60.00 |
|
48.00 |
|
48.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
48.00 |
|
56.00 |
|
56.00 |
|
-0.7113
|
-1.9180
|
-0.9213
|
-1.8810
|
-1.2115
|
1.7734
|
1.1647
|
0.0181
|
-1.2621
|
-0.6280
|
4.0000
|
1.5189
|
0.9735
|
0.1539
|
-0.4549
|
-0.7877
|
-0.3026
|
0.7101
|
1.7863
|
0.7168
0.7244 |
0.7947 |
0.7236 |
0.7895 |
0.7306 |
0.9990 |
0.8889 |
0.7573 |
0.7329 |
0.7259 |
999.0000 |
0.9496 |
0.8602 |
0.7679 |
0.7310 |
0.7236 |
0.7376 |
0.8252 |
1.0016 |
0.8260 |
303
1 Examinee332
1.00 TEST0001
1 Examinee333
1.00 TEST0001
1 Examinee334
1.00 TEST0001
1 Examinee335
1.00 TEST0001
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13
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8
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25
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25
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25
8
25
6
25
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25
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25
11
25
14
25
11
25
6
25
9
|
52.00 |
|
32.00 |
|
56.00 |
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36.00 |
|
48.00 |
|
52.00 |
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56.00 |
|
52.00 |
|
48.00 |
|
52.00 |
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44.00 |
|
32.00 |
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24.00 |
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48.00 |
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28.00 |
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44.00 |
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0.8084 |
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304
1 Examinee352
1.00 TEST0001
1 Examinee353
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10
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10
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25
11
25
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25
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25
13
25
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25
6
25
13
25
12
25
13
25
8
25
10
|
56.00 |
|
40.00 |
|
40.00 |
|
48.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
60.00 |
|
44.00 |
|
48.00 |
|
40.00 |
|
36.00 |
|
52.00 |
|
36.00 |
|
24.00 |
|
52.00 |
|
48.00 |
|
52.00 |
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32.00 |
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-1.0075
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-0.7539
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0.3474
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0.7325 |
0.8912 |
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0.7590 |
0.8198 |
0.7240 |
0.7612 |
0.7705 |
0.7239 |
0.7862 |
0.8625 |
0.8900 |
0.7853 |
0.7371 |
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305
1 Examinee372
1.00 TEST0001
1 Examinee373
1.00 TEST0001
1 Examinee374
1.00 TEST0001
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1.00 TEST0001
1 Examinee376
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11
25
8
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9
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25
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25
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25
13
25
7
25
11
25
13
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15
25
10
25
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25
11
25
8
25
6
25
11
|
44.00 |
|
32.00 |
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36.00 |
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44.00 |
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48.00 |
|
12.00 |
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28.00 |
|
32.00 |
|
52.00 |
|
28.00 |
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44.00 |
|
52.00 |
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60.00 |
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40.00 |
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44.00 |
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-1.4489
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-0.6780
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0.8482 |
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0.7364 |
0.8227 |
0.7443 |
0.7524 |
0.7868 |
0.9424 |
0.7302 |
0.7606 |
0.7548 |
0.7234 |
0.7249 |
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1 Examinee392
1.00 TEST0001
1 Examinee393
1.00 TEST0001
1 Examinee394
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12
25
12
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10
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12
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17
25
11
25
10
25
11
25
6
25
12
25
12
25
9
|
48.00 |
|
48.00 |
|
40.00 |
|
40.00 |
|
28.00 |
|
28.00 |
|
36.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
44.00 |
|
48.00 |
|
68.00 |
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44.00 |
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40.00 |
|
44.00 |
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24.00 |
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48.00 |
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0.3276
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0.7299 |
0.7714 |
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0.7616 |
0.8017 |
0.9382 |
1.1680 |
0.7834 |
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0.7502 |
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1 Examinee412
1.00 TEST0001
1 Examinee413
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25
6
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9
25
12
25
13
25
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25
16
25
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25
13
25
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25
14
25
7
25
8
25
13
25
13
25
7
25
10
25
8
25
10
25
13
|
24.00 |
|
36.00 |
|
48.00 |
|
52.00 |
|
48.00 |
|
28.00 |
|
64.00 |
|
36.00 |
|
52.00 |
|
24.00 |
|
56.00 |
|
28.00 |
|
32.00 |
|
52.00 |
|
52.00 |
|
28.00 |
|
40.00 |
|
32.00 |
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0.4680
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1.0052
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-1.9155
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0.1898
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1.2164
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-2.6695
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0.1466
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0.7727 |
0.7517 |
0.7835 |
0.8800 |
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0.7288 |
1.0721 |
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0.7975 |
0.7396 |
0.8648 |
0.7943 |
0.7242 |
0.7709 |
0.8972 |
0.9434 |
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0.7433 |
0.7286 |
0.7384 |
308
1 Examinee432
1.00 TEST0001
1 Examinee433
1.00 TEST0001
1 Examinee434
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1.00 TEST0001
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25
12
25
8
25
14
25
15
25
6
25
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25
9
25
7
25
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25
13
25
11
25
8
25
13
25
7
25
11
25
12
25
9
25
12
25
10
25
9
|
48.00 |
|
32.00 |
|
56.00 |
|
60.00 |
|
24.00 |
|
48.00 |
|
36.00 |
|
28.00 |
|
28.00 |
|
52.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
28.00 |
|
44.00 |
|
48.00 |
|
36.00 |
|
48.00 |
|
40.00 |
|
36.00 |
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-0.0775
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-0.7139
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1.1774
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1.5744
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-1.6042
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-0.1001
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0.5189
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-1.3529
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-1.3815
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-0.2511
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0.4682
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-0.7820
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1.0793
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0.3691
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0.7818
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0.2264
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0.6735
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0.0288
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-0.5553
0.7506 |
0.7244 |
0.8909 |
0.9599 |
0.7574 |
0.7492 |
0.8029 |
0.7378 |
0.7396 |
0.7403 |
0.7975 |
0.7236 |
0.8757 |
0.7399 |
0.7874 |
0.8342 |
0.7741 |
0.8207 |
0.7581 |
0.7277 |
309
1 Examinee452
1.00 TEST0001
1 Examinee453
1.00 TEST0001
1 Examinee454
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1 Examinee455
1.00 TEST0001
1 Examinee456
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1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
25
13
25
14
25
14
25
9
25
11
25
11
25
10
25
13
25
16
25
11
25
8
25
12
25
9
25
7
25
7
25
11
25
18
25
10
25
8
25
12
|
52.00 |
|
56.00 |
|
56.00 |
|
36.00 |
|
44.00 |
|
44.00 |
|
40.00 |
|
52.00 |
|
64.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
36.00 |
|
28.00 |
|
28.00 |
|
44.00 |
|
72.00 |
|
40.00 |
|
32.00 |
|
48.00 |
|
-0.7026
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1.4824
|
1.2894
|
-0.3498
|
-0.6435
|
-0.3012
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0.7815
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0.6784
|
2.7180
|
-0.6220
|
-1.0372
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0.0983
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-0.3811
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-0.6267
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-1.3039
|
-0.3007
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3.1004
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0.1347
|
-0.8379
|
0.5067
0.7245 |
0.9429 |
0.9092 |
0.7354 |
0.7256 |
0.7377 |
0.8341 |
0.8213 |
1.2199 |
0.7260 |
0.7252 |
0.7634 |
0.7340 |
0.7259 |
0.7351 |
0.7377 |
1.3218 |
0.7663 |
0.7234 |
0.8016 |
310
1 Examinee472
1.00 TEST0001
1 Examinee473
1.00 TEST0001
1 Examinee474
1.00 TEST0001
1 Examinee475
1.00 TEST0001
1 Examinee476
1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
1 Examinee481
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1.00 TEST0001
1 Examinee489
1.00 TEST0001
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1.00 TEST0001
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25
10
25
10
25
10
25
9
25
11
25
8
25
12
25
8
25
9
25
10
25
11
25
10
25
12
25
16
25
10
25
11
25
9
25
14
25
13
25
14
|
40.00 |
|
40.00 |
|
40.00 |
|
36.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
32.00 |
|
36.00 |
|
40.00 |
|
44.00 |
|
40.00 |
|
48.00 |
|
64.00 |
|
40.00 |
|
44.00 |
|
36.00 |
|
56.00 |
|
52.00 |
|
56.00 |
|
0.2588
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-0.0358
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0.0132
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0.1010
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0.2150
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0.0268
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0.2578
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0.2304
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0.0491
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1.9842
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-0.0695
|
0.2082
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0.1277
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0.5767
|
1.6101
|
1.1492
0.7770 |
0.7535 |
0.7570 |
0.7239 |
0.7636 |
0.7358 |
0.7731 |
0.7294 |
0.7580 |
0.7769 |
0.7248 |
0.7745 |
0.7596 |
1.0435 |
0.7512 |
0.7725 |
0.7658 |
0.8094 |
0.9667 |
0.8865 |
311
1 Examinee492
1.00 TEST0001
1 Examinee493
1.00 TEST0001
1 Examinee494
1.00 TEST0001
1 Examinee495
1.00 TEST0001
1 Examinee496
1.00 TEST0001
1 Examinee497
1.00 TEST0001
1 Examinee498
1.00 TEST0001
1 Examinee499
1.00 TEST0001
1 Examinee500
1.00 TEST0001
1 Examinee501
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1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
25
14
25
17
25
13
25
6
25
16
25
12
25
7
25
13
25
10
25
12
25
10
25
6
25
9
25
19
25
14
25
15
25
15
25
12
25
13
25
12
|
56.00 |
|
68.00 |
|
52.00 |
|
24.00 |
|
64.00 |
|
48.00 |
|
28.00 |
|
52.00 |
|
40.00 |
|
48.00 |
|
40.00 |
|
24.00 |
|
36.00 |
|
76.00 |
|
56.00 |
|
60.00 |
|
60.00 |
|
48.00 |
|
52.00 |
|
48.00 |
|
0.6555
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1.9439
|
0.0018
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-1.2602
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1.0227
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0.5076
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-1.7800
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0.7231
|
-0.5105
|
-0.0973
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0.1888
|
-1.1966
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0.1256
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3.6812
|
1.6144
|
1.5559
|
1.2729
|
0.3413
|
0.5782
|
0.1205
0.8185 |
1.0348 |
0.7561 |
0.7328 |
0.8673 |
0.8017 |
0.7765 |
0.8268 |
0.7291 |
0.7493 |
0.7709 |
0.7300 |
0.7656 |
1.4828 |
0.9675 |
0.9565 |
0.9064 |
0.7847 |
0.8096 |
0.7652 |
312
1 Examinee512
1.00 TEST0001
1 Examinee513
1.00 TEST0001
1 Examinee514
1.00 TEST0001
1 Examinee515
1.00 TEST0001
1 Examinee516
1.00 TEST0001
1 Examinee517
1.00 TEST0001
1 Examinee518
1.00 TEST0001
1 Examinee519
1.00 TEST0001
1 Examinee520
1.00 TEST0001
1 Examinee521
1.00 TEST0001
1 Examinee522
1.00 TEST0001
1 Examinee523
1.00 TEST0001
1 Examinee524
1.00 TEST0001
1 Examinee525
1.00 TEST0001
1 Examinee526
1.00 TEST0001
1 Examinee527
1.00 TEST0001
1 Examinee528
1.00 TEST0001
1 Examinee529
1.00 TEST0001
1 Examinee530
1.00 TEST0001
1 Examinee531
1.00 TEST0001
25
12
25
12
25
12
25
12
25
6
25
14
25
13
25
10
25
10
25
11
25
8
25
13
25
13
25
17
25
9
25
8
25
10
25
8
25
9
25
5
|
48.00 |
|
48.00 |
|
48.00 |
|
48.00 |
|
24.00 |
|
56.00 |
|
52.00 |
|
40.00 |
|
40.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
52.00 |
|
68.00 |
|
36.00 |
|
32.00 |
|
40.00 |
|
32.00 |
|
36.00 |
|
20.00 |
|
1.1811
|
-0.0645
|
0.9849
|
0.7743
|
-0.8998
|
1.3749
|
-0.0446
|
0.7466
|
-0.2663
|
0.2900
|
-0.7794
|
0.4286
|
1.1434
|
2.7367
|
-0.7171
|
-0.4916
|
-0.4517
|
-0.7000
|
-0.4158
|
-2.2095
0.8915 |
0.7515 |
0.8618 |
0.8332 |
0.7235 |
0.9238 |
0.7529 |
0.8297 |
0.7395 |
0.7799 |
0.7237 |
0.7934 |
0.8856 |
1.2248 |
0.7243 |
0.7297 |
0.7311 |
0.7246 |
0.7325 |
0.8426 |
313
1 Examinee532
1.00 TEST0001
1 Examinee533
1.00 TEST0001
1 Examinee534
1.00 TEST0001
1 Examinee535
1.00 TEST0001
1 Examinee536
1.00 TEST0001
1 Examinee537
1.00 TEST0001
1 Examinee538
1.00 TEST0001
1 Examinee539
1.00 TEST0001
1 Examinee540
1.00 TEST0001
1 Examinee541
1.00 TEST0001
1 Examinee542
1.00 TEST0001
1 Examinee543
1.00 TEST0001
1 Examinee544
1.00 TEST0001
1 Examinee545
1.00 TEST0001
1 Examinee546
1.00 TEST0001
1 Examinee547
1.00 TEST0001
1 Examinee548
1.00 TEST0001
1 Examinee549
1.00 TEST0001
1 Examinee550
1.00 TEST0001
1 Examinee551
1.00 TEST0001
25
11
25
11
25
9
25
12
25
9
25
12
25
8
25
13
25
7
25
15
25
16
25
9
25
10
25
10
25
13
25
7
25
5
25
10
25
4
25
4
|
44.00 |
|
44.00 |
|
36.00 |
|
48.00 |
|
36.00 |
|
48.00 |
|
32.00 |
|
52.00 |
|
28.00 |
|
60.00 |
|
64.00 |
|
36.00 |
|
40.00 |
|
40.00 |
|
52.00 |
|
28.00 |
|
20.00 |
|
40.00 |
|
16.00 |
|
16.00 |
|
-0.0310
|
1.0579
|
-0.5624
|
0.6236
|
-0.4125
|
1.7356
|
-0.9099
|
0.9162
|
-1.4614
|
2.8972
|
3.0336
|
-0.7161
|
-0.6319
|
0.0981
|
1.0480
|
-2.2058
|
-2.8293
|
-0.2260
|
-2.9880
|
-3.8413
0.7538 |
0.8725 |
0.7275 |
0.8148 |
0.7327 |
0.9913 |
0.7236 |
0.8521 |
0.7452 |
1.2671 |
1.3037 |
0.7243 |
0.7258 |
0.7634 |
0.8711 |
0.8419 |
0.9853 |
0.7416 |
1.0303 |
1.3235 |
314
1 Examinee552
1.00 TEST0001
1 Examinee553
1.00 TEST0001
1 Examinee554
1.00 TEST0001
1 Examinee555
1.00 TEST0001
1 Examinee556
1.00 TEST0001
1 Examinee557
1.00 TEST0001
1 Examinee558
1.00 TEST0001
1 Examinee559
1.00 TEST0001
1 Examinee560
1.00 TEST0001
1 Examinee561
1.00 TEST0001
1 Examinee562
1.00 TEST0001
1 Examinee563
1.00 TEST0001
1 Examinee564
1.00 TEST0001
1 Examinee565
1.00 TEST0001
1 Examinee566
1.00 TEST0001
1 Examinee567
1.00 TEST0001
1 Examinee568
1.00 TEST0001
1 Examinee569
1.00 TEST0001
1 Examinee570
1.00 TEST0001
1 Examinee571
1.00 TEST0001
25
6
25
6
25
5
25
7
25
7
25
2
25
3
25
6
25
2
25
5
25
8
25
7
25
8
25
9
25
8
25
9
25
3
25
4
25
7
25
5
|
24.00 |
|
24.00 |
|
20.00 |
|
28.00 |
|
28.00 |
|
8.00 |
|
12.00 |
|
24.00 |
|
8.00 |
|
20.00 |
|
32.00 |
|
28.00 |
|
32.00 |
|
36.00 |
|
32.00 |
|
36.00 |
|
12.00 |
|
16.00 |
|
28.00 |
|
20.00 |
|
-2.4225 0.8855 |
|
-2.2577 0.8517 |
|
-2.6303 0.9337 |
|
-3.0049 1.0352 |
|
-1.6672 0.7637 |
|
-3.9785 1.3782 |
|
-3.8758 1.3370 |
|
-2.6670 0.9428 |
|
-4.0000 999.0000 |
|
-3.5564 1.2164 |
|
-1.7400 0.7717 |
|
-1.2491 0.7323 |
|
-2.1046 0.8239 |
|
-0.9775 0.7242 |
|
-1.8741 0.7886 |
|
-2.2119 0.8430 |
|
-2.9499 1.0192 |
|
-2.4395 0.8892 |
|
-2.3207 0.8642 |
|
-2.7762 0.9711 |
315
1 Examinee572
1.00 TEST0001
1 Examinee573
1.00 TEST0001
1 Examinee574
1.00 TEST0001
1 Examinee575
1.00 TEST0001
1 Examinee576
1.00 TEST0001
1 Examinee577
1.00 TEST0001
1 Examinee578
1.00 TEST0001
1 Examinee579
1.00 TEST0001
1 Examinee580
1.00 TEST0001
1 Examinee581
1.00 TEST0001
1 Examinee582
1.00 TEST0001
1 Examinee583
1.00 TEST0001
1 Examinee584
1.00 TEST0001
1 Examinee585
1.00 TEST0001
1 Examinee586
1.00 TEST0001
1 Examinee587
1.00 TEST0001
1 Examinee588
1.00 TEST0001
1 Examinee589
1.00 TEST0001
1 Examinee590
1.00 TEST0001
1 Examinee591
1.00 TEST0001
25
3
25
6
25
4
25
8
25
2
25
3
25
10
25
1
25
10
25
8
25
12
25
8
25
10
25
14
25
9
25
12
25
12
25
14
25
8
25
13
|
|
12.00 | -4.0000 999.0000 |
|
|
24.00 | -3.0282 1.0421 |
|
|
16.00 | -2.9176 1.0099 |
|
|
32.00 | -1.7232 0.7698 |
|
|
8.00 | -4.0000 999.0000 |
|
|
12.00 | -3.5921 1.2293 |
|
|
40.00 | -1.2938 0.7345 |
|
|
4.00 | -4.0000 999.0000 |
|
|
40.00 | 0.4647 0.7971 |
|
|
32.00 | 0.0153 0.7571 |
|
|
48.00 | 0.4129 0.7918 |
|
|
32.00 | -0.8320 0.7234 |
|
|
40.00 | 0.2092 0.7726 |
|
|
56.00 | 0.5850 0.8103 |
|
|
36.00 | -0.7056 0.7245 |
|
|
48.00 | 0.7506 0.8302 |
|
|
48.00 | 0.3695 0.7875 |
|
|
56.00 | 1.7928 1.0029 |
|
|
32.00 | -0.9692 0.7241 |
|
|
52.00 | 0.4963 0.8005 |
316
1 Examinee592
1.00 TEST0001
1 Examinee593
1.00 TEST0001
1 Examinee594
1.00 TEST0001
1 Examinee595
1.00 TEST0001
1 Examinee596
1.00 TEST0001
1 Examinee597
1.00 TEST0001
1 Examinee598
1.00 TEST0001
1 Examinee599
1.00 TEST0001
1 Examinee600
1.00 TEST0001
1 Examinee601
1.00 TEST0001
1 Examinee602
1.00 TEST0001
1 Examinee603
1.00 TEST0001
1 Examinee604
1.00 TEST0001
1 Examinee605
1.00 TEST0001
1 Examinee606
1.00 TEST0001
1 Examinee607
1.00 TEST0001
1 Examinee608
1.00 TEST0001
1 Examinee609
1.00 TEST0001
1 Examinee610
1.00 TEST0001
1 Examinee611
1.00 TEST0001
25
7
25
15
25
12
25
12
25
8
25
14
25
7
25
8
25
11
25
9
25
12
25
9
25
12
25
8
25
7
25
10
25
6
25
13
25
9
25
13
|
28.00 |
|
60.00 |
|
48.00 |
|
48.00 |
|
32.00 |
|
56.00 |
|
28.00 |
|
32.00 |
|
44.00 |
|
36.00 |
|
48.00 |
|
36.00 |
|
48.00 |
|
32.00 |
|
28.00 |
|
40.00 |
|
24.00 |
|
52.00 |
|
36.00 |
|
52.00 |
|
-0.9429
|
0.8084
|
-0.1917
|
-0.1394
|
-1.4313
|
1.3773
|
-1.5387
|
-0.8045
|
0.7621
|
-1.0728
|
-0.3907
|
-1.1211
|
0.3508
|
-1.6562
|
-1.3523
|
-0.1650
|
-1.1743
|
1.2481
|
-0.3082
|
-0.3713
0.7238 |
0.8376 |
0.7436 |
0.7467 |
0.7430 |
0.9242 |
0.7514 |
0.7235 |
0.8317 |
0.7261 |
0.7336 |
0.7274 |
0.7856 |
0.7626 |
0.7378 |
0.7451 |
0.7292 |
0.9023 |
0.7373 |
0.7344 |
317
1 Examinee612
1.00 TEST0001
1 Examinee613
1.00 TEST0001
1 Examinee614
1.00 TEST0001
1 Examinee615
1.00 TEST0001
1 Examinee616
1.00 TEST0001
1 Examinee617
1.00 TEST0001
1 Examinee618
1.00 TEST0001
1 Examinee619
1.00 TEST0001
1 Examinee620
1.00 TEST0001
1 Examinee621
1.00 TEST0001
1 Examinee622
1.00 TEST0001
1 Examinee623
1.00 TEST0001
1 Examinee624
1.00 TEST0001
1 Examinee625
1.00 TEST0001
1 Examinee626
1.00 TEST0001
1 Examinee627
1.00 TEST0001
1 Examinee628
1.00 TEST0001
1 Examinee629
1.00 TEST0001
1 Examinee630
1.00 TEST0001
1 Examinee631
1.00 TEST0001
25
2
25
13
25
11
25
12
25
8
25
13
25
15
25
10
25
8
25
8
25
10
25
9
25
14
25
11
25
11
25
16
25
10
25
6
25
9
25
14
|
|
8.00 | -3.1172
|
|
52.00 | 1.1633
|
|
44.00 | 0.1380
|
|
48.00 | 0.7531
|
|
32.00 | -1.2515
|
|
52.00 | 0.3954
|
|
60.00 | 1.9523
|
|
40.00 | 0.0625
|
|
32.00 | -1.1930
|
|
32.00 | -0.9511
|
|
40.00 | 0.5528
|
|
36.00 | -1.1961
|
|
56.00 | 1.9160
|
|
44.00 | 0.5728
|
|
44.00 | 0.1694
|
|
64.00 | 2.0427
|
|
40.00 | -0.0199
|
|
24.00 | -1.2906
|
|
36.00 | -0.3973
|
|
56.00 | 1.5390
1.0691 |
0.8887 |
0.7666 |
0.8305 |
0.7324 |
0.7900 |
1.0366 |
0.7606 |
0.7299 |
0.7239 |
0.8067 |
0.7300 |
1.0288 |
0.8089 |
0.7692 |
1.0564 |
0.7546 |
0.7344 |
0.7333 |
0.9533 |
318
1 Examinee632
1.00 TEST0001
1 Examinee633
1.00 TEST0001
1 Examinee634
1.00 TEST0001
1 Examinee635
1.00 TEST0001
1 Examinee636
1.00 TEST0001
1 Examinee637
1.00 TEST0001
1 Examinee638
1.00 TEST0001
1 Examinee639
1.00 TEST0001
1 Examinee640
1.00 TEST0001
1 Examinee641
1.00 TEST0001
1 Examinee642
1.00 TEST0001
1 Examinee643
1.00 TEST0001
1 Examinee644
1.00 TEST0001
1 Examinee645
1.00 TEST0001
1 Examinee646
1.00 TEST0001
1 Examinee647
1.00 TEST0001
1 Examinee648
1.00 TEST0001
1 Examinee649
1.00 TEST0001
1 Examinee650
1.00 TEST0001
1 Examinee651
1.00 TEST0001
25
11
25
15
25
8
25
12
25
12
25
13
25
18
25
10
25
11
25
12
25
9
25
6
25
15
25
8
25
6
25
7
25
8
25
13
25
9
25
15
|
44.00 |
|
60.00 |
|
32.00 |
|
48.00 |
|
48.00 |
|
52.00 |
|
72.00 |
|
40.00 |
|
44.00 |
|
48.00 |
|
36.00 |
|
24.00 |
|
60.00 |
|
32.00 |
|
24.00 |
|
28.00 |
|
32.00 |
|
52.00 |
|
36.00 |
|
60.00 |
|
-0.2352
|
2.1714
|
-1.3901
|
0.4843
|
0.4669
|
0.7037
|
4.0000
|
0.0221
|
-0.4909
|
0.6264
|
-0.5322
|
-1.1780
|
0.0539
|
-0.8710
|
-1.5848
|
-1.0474
|
-0.7792
|
0.7717
|
-0.4365
|
1.6466
0.7411 |
1.0855 |
0.7402 |
0.7992 |
0.7974 |
0.8244 |
999.0000 |
0.7576 |
0.7297 |
0.8151 |
0.7284 |
0.7293 |
0.7600 |
0.7234 |
0.7556 |
0.7255 |
0.7237 |
0.8329 |
0.7317 |
0.9738 |
319
1 Examinee652
1.00 TEST0001
1 Examinee653
1.00 TEST0001
1 Examinee654
1.00 TEST0001
1 Examinee655
1.00 TEST0001
1 Examinee656
1.00 TEST0001
1 Examinee657
1.00 TEST0001
1 Examinee658
1.00 TEST0001
1 Examinee659
1.00 TEST0001
1 Examinee660
1.00 TEST0001
1 Examinee661
1.00 TEST0001
1 Examinee662
1.00 TEST0001
1 Examinee663
1.00 TEST0001
1 Examinee664
1.00 TEST0001
1 Examinee665
1.00 TEST0001
1 Examinee666
1.00 TEST0001
1 Examinee667
1.00 TEST0001
1 Examinee668
1.00 TEST0001
1 Examinee669
1.00 TEST0001
1 Examinee670
1.00 TEST0001
1 Examinee671
1.00 TEST0001
25
8
25
17
25
19
25
6
25
8
25
10
25
13
25
6
25
14
25
8
25
9
25
8
25
12
25
6
25
10
25
9
25
12
25
9
25
13
25
17
|
32.00 |
|
68.00 |
|
76.00 |
|
24.00 |
|
32.00 |
|
40.00 |
|
52.00 |
|
24.00 |
|
56.00 |
|
32.00 |
|
36.00 |
|
32.00 |
|
48.00 |
|
24.00 |
|
40.00 |
|
36.00 |
|
48.00 |
|
36.00 |
|
52.00 |
|
68.00 |
|
-0.0778
|
3.5894
|
4.0000
|
-1.0241
|
-1.2359
|
0.5148
|
1.0968
|
-1.8585
|
1.7186
|
-0.6300
|
-0.5124
|
-0.1584
|
-0.1604
|
-1.6714
|
-0.0242
|
-0.4402
|
0.1124
|
-0.2317
|
1.1533
|
2.1664
0.7506 |
1.4571 |
999.0000 |
0.7250 |
0.7317 |
0.8025 |
0.8784 |
0.7865 |
0.9879 |
0.7259 |
0.7290 |
0.7455 |
0.7454 |
0.7642 |
0.7543 |
0.7316 |
0.7645 |
0.7413 |
0.8871 |
1.0844 |
320
1 Examinee672
1.00 TEST0001
1 Examinee673
1.00 TEST0001
1 Examinee674
1.00 TEST0001
1 Examinee675
1.00 TEST0001
1 Examinee676
1.00 TEST0001
1 Examinee677
1.00 TEST0001
1 Examinee678
1.00 TEST0001
1 Examinee679
1.00 TEST0001
1 Examinee680
1.00 TEST0001
1 Examinee681
1.00 TEST0001
1 Examinee682
1.00 TEST0001
1 Examinee683
1.00 TEST0001
1 Examinee684
1.00 TEST0001
1 Examinee685
1.00 TEST0001
1 Examinee686
1.00 TEST0001
1 Examinee687
1.00 TEST0001
1 Examinee688
1.00 TEST0001
1 Examinee689
1.00 TEST0001
1 Examinee690
1.00 TEST0001
1 Examinee691
1.00 TEST0001
25
13
25
16
25
11
25
10
25
15
25
12
25
13
25
10
25
15
25
6
25
14
25
10
25
14
25
13
25
5
25
9
25
16
25
8
25
16
25
13
|
52.00 |
|
64.00 |
|
44.00 |
|
40.00 |
|
60.00 |
|
48.00 |
|
52.00 |
|
40.00 |
|
60.00 |
|
24.00 |
|
56.00 |
|
40.00 |
|
56.00 |
|
52.00 |
|
20.00 |
|
36.00 |
|
64.00 |
|
32.00 |
|
64.00 |
|
52.00 |
|
1.4975
|
1.4668
|
-0.2582
|
0.2959
|
1.7752
|
-0.3631
|
0.5807
|
-0.5801
|
1.4493
|
-2.3415
|
1.6295
|
0.1079
|
1.3900
|
1.6668
|
-1.7525
|
-0.2334
|
1.7807
|
-0.6546
|
2.2823
|
1.1749
0.9456 |
0.9401 |
0.7399 |
0.7804 |
0.9994 |
0.7348 |
0.8098 |
0.7270 |
0.9369 |
0.8684 |
0.9705 |
0.7642 |
0.9264 |
0.9777 |
0.7732 |
0.7412 |
1.0005 |
0.7253 |
1.1115 |
0.8905 |
321
1 Examinee692
1.00 TEST0001
1 Examinee693
1.00 TEST0001
1 Examinee694
1.00 TEST0001
1 Examinee695
1.00 TEST0001
1 Examinee696
1.00 TEST0001
1 Examinee697
1.00 TEST0001
1 Examinee698
1.00 TEST0001
1 Examinee699
1.00 TEST0001
1 Examinee700
1.00 TEST0001
1 Examinee701
1.00 TEST0001
1 Examinee702
1.00 TEST0001
1 Examinee703
1.00 TEST0001
1 Examinee704
1.00 TEST0001
1 Examinee705
1.00 TEST0001
1 Examinee706
1.00 TEST0001
1 Examinee707
1.00 TEST0001
1 Examinee708
1.00 TEST0001
1 Examinee709
1.00 TEST0001
1 Examinee710
1.00 TEST0001
1 Examinee711
1.00 TEST0001
25
8
25
11
25
10
25
14
25
8
25
9
25
11
25
7
25
7
25
13
25
10
25
7
25
10
25
8
25
11
25
11
25
15
25
13
25
14
25
13
|
32.00 |
|
44.00 |
|
40.00 |
|
56.00 |
|
32.00 |
|
36.00 |
|
44.00 |
|
28.00 |
|
28.00 |
|
52.00 |
|
40.00 |
|
28.00 |
|
40.00 |
|
32.00 |
|
44.00 |
|
44.00 |
|
60.00 |
|
52.00 |
|
56.00 |
|
52.00 |
|
-0.9418
|
-0.2668
|
0.3899
|
2.5505
|
-0.4397
|
-1.1243
|
0.1933
|
-1.0558
|
-1.5791
|
0.9976
|
-0.4563
|
-0.8582
|
-1.6301
|
-0.2378
|
-0.4591
|
-0.3578
|
2.2477
|
1.9177
|
0.8618
|
1.6240
0.7238 |
0.7394 |
0.7895 |
1.1771 |
0.7316 |
0.7275 |
0.7712 |
0.7257 |
0.7550 |
0.8637 |
0.7310 |
0.7234 |
0.7599 |
0.7410 |
0.7309 |
0.7350 |
1.1033 |
1.0291 |
0.8447 |
0.9694 |
322
1 Examinee712
1.00 TEST0001
1 Examinee713
1.00 TEST0001
1 Examinee714
1.00 TEST0001
1 Examinee715
1.00 TEST0001
1 Examinee716
1.00 TEST0001
1 Examinee717
1.00 TEST0001
1 Examinee718
1.00 TEST0001
1 Examinee719
1.00 TEST0001
1 Examinee720
1.00 TEST0001
1 Examinee721
1.00 TEST0001
1 Examinee722
1.00 TEST0001
1 Examinee723
1.00 TEST0001
1 Examinee724
1.00 TEST0001
1 Examinee725
1.00 TEST0001
1 Examinee726
1.00 TEST0001
1 Examinee727
1.00 TEST0001
1 Examinee728
1.00 TEST0001
1 Examinee729
1.00 TEST0001
1 Examinee730
1.00 TEST0001
1 Examinee731
1.00 TEST0001
25
10
25
14
25
9
25
11
25
10
25
10
25
13
25
11
25
11
25
17
25
9
25
11
25
13
25
5
25
12
25
10
25
11
25
11
25
7
25
13
|
40.00 |
|
56.00 |
|
36.00 |
|
44.00 |
|
40.00 |
|
40.00 |
|
52.00 |
|
44.00 |
|
44.00 |
|
68.00 |
|
36.00 |
|
44.00 |
|
52.00 |
|
20.00 |
|
48.00 |
|
40.00 |
|
44.00 |
|
44.00 |
|
28.00 |
|
52.00 |
|
-0.2022
|
0.8670
|
-0.1908
|
0.2167
|
-0.6660
|
-0.6822
|
0.7458
|
-0.8724
|
-0.3430
|
2.7316
|
-0.7964
|
-0.1443
|
0.0743
|
-1.6835
|
1.0282
|
-0.2661
|
0.4109
|
1.0023
|
-1.0186
|
1.9608
0.7430 |
0.8454 |
0.7436 |
0.7733 |
0.7251 |
0.7248 |
0.8296 |
0.7234 |
0.7357 |
1.2235 |
0.7235 |
0.7464 |
0.7615 |
0.7654 |
0.8681 |
0.7395 |
0.7916 |
0.8643 |
0.7249 |
1.0384 |
323
1 Examinee732
1.00 TEST0001
1 Examinee733
1.00 TEST0001
1 Examinee734
1.00 TEST0001
1 Examinee735
1.00 TEST0001
1 Examinee736
1.00 TEST0001
1 Examinee737
1.00 TEST0001
1 Examinee738
1.00 TEST0001
1 Examinee739
1.00 TEST0001
1 Examinee740
1.00 TEST0001
1 Examinee741
1.00 TEST0001
1 Examinee742
1.00 TEST0001
1 Examinee743
1.00 TEST0001
1 Examinee744
1.00 TEST0001
1 Examinee745
1.00 TEST0001
1 Examinee746
1.00 TEST0001
1 Examinee747
1.00 TEST0001
1 Examinee748
1.00 TEST0001
1 Examinee749
1.00 TEST0001
1 Examinee750
1.00 TEST0001
1 Examinee751
1.00 TEST0001
25
14
25
12
25
12
25
12
25
9
25
13
25
7
25
13
25
9
25
11
25
8
25
12
25
14
25
14
25
11
25
11
25
10
25
9
25
12
25
4
|
56.00 |
|
48.00 |
|
48.00 |
|
48.00 |
|
36.00 |
|
52.00 |
|
28.00 |
|
52.00 |
|
36.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
56.00 |
|
56.00 |
|
44.00 |
|
44.00 |
|
40.00 |
|
36.00 |
|
48.00 |
|
16.00 |
|
1.0197
|
0.7845
|
0.1065
|
1.2164
|
-0.4878
|
1.8328
|
-1.6160
|
0.9918
|
0.0862
|
-0.3351
|
-0.9384
|
1.0118
|
0.4767
|
1.7039
|
0.1764
|
0.0393
|
-1.4741
|
-0.2008
|
0.5249
|
-3.0961
0.8669 |
0.8345 |
0.7641 |
0.8972 |
0.7298 |
1.0112 |
0.7585 |
0.8628 |
0.7625 |
0.7361 |
0.7238 |
0.8657 |
0.7984 |
0.9850 |
0.7698 |
0.7589 |
0.7462 |
0.7430 |
0.8036 |
1.0626 |
324
1 Examinee752
1.00 TEST0001
1 Examinee753
1.00 TEST0001
1 Examinee754
1.00 TEST0001
1 Examinee755
1.00 TEST0001
1 Examinee756
1.00 TEST0001
1 Examinee757
1.00 TEST0001
1 Examinee758
1.00 TEST0001
1 Examinee759
1.00 TEST0001
1 Examinee760
1.00 TEST0001
1 Examinee761
1.00 TEST0001
1 Examinee762
1.00 TEST0001
1 Examinee763
1.00 TEST0001
1 Examinee764
1.00 TEST0001
1 Examinee765
1.00 TEST0001
1 Examinee766
1.00 TEST0001
1 Examinee767
1.00 TEST0001
1 Examinee768
1.00 TEST0001
1 Examinee769
1.00 TEST0001
1 Examinee770
1.00 TEST0001
1 Examinee771
1.00 TEST0001
25
12
25
5
25
11
25
9
25
13
25
5
25
13
25
11
25
4
25
13
25
9
25
10
25
8
25
8
25
11
25
10
25
6
25
10
25
19
25
14
|
48.00 |
|
20.00 |
|
44.00 |
|
36.00 |
|
52.00 |
|
20.00 |
|
52.00 |
|
44.00 |
|
16.00 |
|
52.00 |
|
36.00 |
|
40.00 |
|
32.00 |
|
32.00 |
|
44.00 |
|
40.00 |
|
24.00 |
|
40.00 |
|
76.00 |
|
56.00 |
|
0.4456
|
-1.6749
|
-0.1024
|
-1.3522
|
0.4311
|
-1.1259
|
1.0660
|
0.6967
|
-2.4664
|
1.0439
|
-0.6589
|
-0.2632
|
-0.3239
|
-1.3722
|
-0.0668
|
-0.2104
|
-0.7543
|
-0.2376
|
4.0000
|
1.6136
0.7951 |
0.7645 |
0.7490 |
0.7378 |
0.7936 |
0.7275 |
0.8737 |
0.8235 |
0.8952 |
0.8704 |
0.7253 |
0.7396 |
0.7366 |
0.7390 |
0.7514 |
0.7425 |
0.7239 |
0.7410 |
999.0000 |
0.9674 |
325
1 Examinee772
1.00 TEST0001
1 Examinee773
1.00 TEST0001
1 Examinee774
1.00 TEST0001
1 Examinee775
1.00 TEST0001
1 Examinee776
1.00 TEST0001
1 Examinee777
1.00 TEST0001
1 Examinee778
1.00 TEST0001
1 Examinee779
1.00 TEST0001
1 Examinee780
1.00 TEST0001
1 Examinee781
1.00 TEST0001
1 Examinee782
1.00 TEST0001
1 Examinee783
1.00 TEST0001
1 Examinee784
1.00 TEST0001
1 Examinee785
1.00 TEST0001
1 Examinee786
1.00 TEST0001
1 Examinee787
1.00 TEST0001
1 Examinee788
1.00 TEST0001
1 Examinee789
1.00 TEST0001
1 Examinee790
1.00 TEST0001
1 Examinee791
1.00 TEST0001
25
19
25
13
25
11
25
11
25
12
25
15
25
11
25
14
25
14
25
5
25
10
25
15
25
9
25
4
25
7
25
10
25
14
25
16
25
12
25
14
|
76.00 |
|
52.00 |
|
44.00 |
|
44.00 |
|
48.00 |
|
60.00 |
|
44.00 |
|
56.00 |
|
56.00 |
|
20.00 |
|
40.00 |
|
60.00 |
|
36.00 |
|
16.00 |
|
28.00 |
|
40.00 |
|
56.00 |
|
64.00 |
|
48.00 |
|
56.00 |
|
4.0000
|
0.3329
|
0.6836
|
-0.4636
|
0.0354
|
1.8732
|
-0.3909
|
0.8272
|
0.1731
|
-2.7002
|
0.0827
|
2.2407
|
-0.6876
|
-2.5127
|
-1.1507
|
-0.1843
|
1.2227
|
3.3731
|
0.2257
|
0.3031
999.0000 |
0.7839 |
0.8219 |
0.7307 |
0.7586 |
1.0197 |
0.7336 |
0.8401 |
0.7695 |
0.9512 |
0.7622 |
1.1017 |
0.7248 |
0.9057 |
0.7283 |
0.7440 |
0.8982 |
1.3969 |
0.7741 |
0.7811 |
326
1 Examinee792
1.00 TEST0001
1 Examinee793
1.00 TEST0001
1 Examinee794
1.00 TEST0001
1 Examinee795
1.00 TEST0001
1 Examinee796
1.00 TEST0001
1 Examinee797
1.00 TEST0001
1 Examinee798
1.00 TEST0001
1 Examinee799
1.00 TEST0001
1 Examinee800
1.00 TEST0001
1 Examinee801
1.00 TEST0001
1 Examinee802
1.00 TEST0001
1 Examinee803
1.00 TEST0001
1 Examinee804
1.00 TEST0001
1 Examinee805
1.00 TEST0001
1 Examinee806
1.00 TEST0001
1 Examinee807
1.00 TEST0001
1 Examinee808
1.00 TEST0001
1 Examinee809
1.00 TEST0001
1 Examinee810
1.00 TEST0001
1 Examinee811
1.00 TEST0001
25
9
25
7
25
12
25
9
25
9
25
12
25
9
25
10
25
14
25
12
25
16
25
14
25
14
25
17
25
17
25
17
25
5
25
14
25
14
25
19
|
36.00 |
|
28.00 |
|
48.00 |
|
36.00 |
|
36.00 |
|
48.00 |
|
36.00 |
|
40.00 |
|
56.00 |
|
48.00 |
|
64.00 |
|
56.00 |
|
56.00 |
|
68.00 |
|
68.00 |
|
68.00 |
|
20.00 |
|
56.00 |
|
56.00 |
|
76.00 |
|
0.0012
|
-0.9904
|
-0.6108
|
-0.4376
|
-0.8084
|
1.0132
|
0.1212
|
-0.0642
|
2.0422
|
-0.2314
|
2.4846
|
0.9907
|
-0.0081
|
0.7905
|
2.6100
|
3.2354
|
-2.4783
|
1.8859
|
1.7998
|
4.0000
0.7561 |
0.7244 |
0.7263 |
0.7317 |
0.7235 |
0.8659 |
0.7652 |
0.7515 |
1.0563 |
0.7413 |
1.1606 |
0.8627 |
0.7554 |
0.8353 |
1.1922 |
1.3588 |
0.8978 |
1.0224 |
1.0044 |
999.0000 |
327
1 Examinee812
1.00 TEST0001
1 Examinee813
1.00 TEST0001
1 Examinee814
1.00 TEST0001
1 Examinee815
1.00 TEST0001
1 Examinee816
1.00 TEST0001
1 Examinee817
1.00 TEST0001
1 Examinee818
1.00 TEST0001
1 Examinee819
1.00 TEST0001
1 Examinee820
1.00 TEST0001
1 Examinee821
1.00 TEST0001
1 Examinee822
1.00 TEST0001
1 Examinee823
1.00 TEST0001
1 Examinee824
1.00 TEST0001
1 Examinee825
1.00 TEST0001
1 Examinee826
1.00 TEST0001
1 Examinee827
1.00 TEST0001
1 Examinee828
1.00 TEST0001
1 Examinee829
1.00 TEST0001
1 Examinee830
1.00 TEST0001
1 Examinee831
1.00 TEST0001
25
3
25
15
25
14
25
8
25
9
25
2
25
7
25
3
25
3
25
5
25
9
25
7
25
8
25
6
25
6
25
4
25
6
25
5
25
6
25
5
|
|
12.00 | -3.0242
|
|
60.00 | 1.2853
|
|
56.00 | 1.2815
|
|
32.00 | -1.9720
|
|
36.00 | -1.9289
|
|
8.00 | -3.8327
|
|
28.00 | -1.6143
|
|
12.00 | -3.7929
|
|
12.00 | -3.3656
|
|
20.00 | -2.8368
|
|
36.00 | -1.2270
|
|
28.00 | -2.5899
|
|
32.00 | -1.8395
|
|
24.00 | -2.3315
|
|
24.00 | -2.4184
|
|
16.00 | -2.9884
|
|
24.00 | -2.8242
|
|
20.00 | -2.5842
|
|
24.00 | -2.0362
|
|
20.00 | -3.1552
1.0409 |
0.9085 |
0.9079 |
0.8026 |
0.7963 |
1.3201 |
0.7584 |
1.3047 |
1.1497 |
0.9874 |
0.7313 |
0.9238 |
0.7840 |
0.8664 |
0.8846 |
1.0304 |
0.9839 |
0.9225 |
0.8126 |
1.0810 |
328
1 Examinee832
1.00 TEST0001
1 Examinee833
1.00 TEST0001
1 Examinee834
1.00 TEST0001
1 Examinee835
1.00 TEST0001
1 Examinee836
1.00 TEST0001
1 Examinee837
1.00 TEST0001
1 Examinee838
1.00 TEST0001
1 Examinee839
1.00 TEST0001
1 Examinee840
1.00 TEST0001
1 Examinee841
1.00 TEST0001
1 Examinee842
1.00 TEST0001
1 Examinee843
1.00 TEST0001
1 Examinee844
1.00 TEST0001
1 Examinee845
1.00 TEST0001
1 Examinee846
1.00 TEST0001
1 Examinee847
1.00 TEST0001
1 Examinee848
1.00 TEST0001
1 Examinee849
1.00 TEST0001
1 Examinee850
1.00 TEST0001
1 Examinee851
1.00 TEST0001
25
3
25
7
25
5
25
8
25
10
25
11
25
5
25
4
25
8
25
5
25
5
25
9
25
17
25
17
25
15
25
13
25
12
25
8
25
14
25
10
|
12.00 |
|
28.00 |
|
20.00 |
|
32.00 |
|
40.00 |
|
44.00 |
|
20.00 |
|
16.00 |
|
32.00 |
|
20.00 |
|
20.00 |
|
36.00 |
|
68.00 |
|
68.00 |
|
60.00 |
|
52.00 |
|
48.00 |
|
32.00 |
|
56.00 |
|
40.00 |
|
-4.0000 999.0000 |
|
-2.5480 0.9139 |
|
-2.7016 0.9516 |
|
-1.6893 0.7661 |
|
-1.4330 0.7431 |
|
-1.0204 0.7249 |
|
-2.3037 0.8607 |
|
-2.8036 0.9784 |
|
-1.2424 0.7320 |
|
-2.4496 0.8914 |
|
-2.0181 0.8097 |
|
-0.6674 0.7251 |
|
1.5087 0.9477 |
|
1.9996 1.0469 |
|
3.1387 1.3323 |
|
0.2047 0.7722 |
|
0.5350 0.8047 |
|
-1.8533 0.7858 |
|
0.9817 0.8614 |
|
-0.3003 0.7377 |
329
1 Examinee852
1.00 TEST0001
1 Examinee853
1.00 TEST0001
1 Examinee854
1.00 TEST0001
1 Examinee855
1.00 TEST0001
1 Examinee856
1.00 TEST0001
1 Examinee857
1.00 TEST0001
1 Examinee858
1.00 TEST0001
1 Examinee859
1.00 TEST0001
1 Examinee860
1.00 TEST0001
1 Examinee861
1.00 TEST0001
1 Examinee862
1.00 TEST0001
1 Examinee863
1.00 TEST0001
1 Examinee864
1.00 TEST0001
1 Examinee865
1.00 TEST0001
1 Examinee866
1.00 TEST0001
1 Examinee867
1.00 TEST0001
1 Examinee868
1.00 TEST0001
1 Examinee869
1.00 TEST0001
1 Examinee870
1.00 TEST0001
1 Examinee871
1.00 TEST0001
25
13
25
16
25
11
25
13
25
11
25
13
25
17
25
12
25
10
25
7
25
12
25
8
25
10
25
14
25
8
25
3
25
5
25
5
25
15
25
10
|
52.00 |
|
64.00 |
|
44.00 |
|
52.00 |
|
44.00 |
|
52.00 |
|
68.00 |
|
48.00 |
|
40.00 |
|
28.00 |
|
48.00 |
|
32.00 |
|
40.00 |
|
56.00 |
|
32.00 |
|
12.00 |
|
20.00 |
|
20.00 |
|
60.00 |
|
40.00 |
|
0.1488
|
3.1561
|
-0.6892
|
1.2589
|
0.3793
|
0.0831
|
1.8228
|
0.1146
|
-0.8014
|
-0.8277
|
0.0977
|
-1.0568
|
0.0054
|
1.0543
|
-0.6808
|
-2.4435
|
-1.1410
|
-2.6043
|
0.9923
|
0.4451
0.7675 |
1.3371 |
0.7247 |
0.9041 |
0.7884 |
0.7622 |
1.0091 |
0.7647 |
0.7235 |
0.7234 |
0.7634 |
0.7257 |
0.7564 |
0.8720 |
0.7249 |
0.8901 |
0.7280 |
0.9273 |
0.8629 |
0.7951 |
330
1 Examinee872
1.00 TEST0001
1 Examinee873
1.00 TEST0001
1 Examinee874
1.00 TEST0001
1 Examinee875
1.00 TEST0001
1 Examinee876
1.00 TEST0001
1 Examinee877
1.00 TEST0001
1 Examinee878
1.00 TEST0001
1 Examinee879
1.00 TEST0001
1 Examinee880
1.00 TEST0001
1 Examinee881
1.00 TEST0001
1 Examinee882
1.00 TEST0001
1 Examinee883
1.00 TEST0001
1 Examinee884
1.00 TEST0001
1 Examinee885
1.00 TEST0001
1 Examinee886
1.00 TEST0001
1 Examinee887
1.00 TEST0001
1 Examinee888
1.00 TEST0001
1 Examinee889
1.00 TEST0001
1 Examinee890
1.00 TEST0001
1 Examinee891
1.00 TEST0001
25
6
25
10
25
9
25
13
25
9
25
10
25
5
25
13
25
10
25
7
25
5
25
14
25
11
25
9
25
11
25
9
25
7
25
10
25
13
25
14
|
24.00 |
|
40.00 |
|
36.00 |
|
52.00 |
|
36.00 |
|
40.00 |
|
20.00 |
|
52.00 |
|
40.00 |
|
28.00 |
|
20.00 |
|
56.00 |
|
44.00 |
|
36.00 |
|
44.00 |
|
36.00 |
|
28.00 |
|
40.00 |
|
52.00 |
|
56.00 |
|
-1.3596
|
-0.5653
|
-0.0521
|
0.4765
|
-0.1765
|
0.1721
|
-2.3869
|
1.6313
|
-0.0073
|
-1.4316
|
-1.9269
|
1.5013
|
0.7298
|
-0.6194
|
0.5733
|
-0.8930
|
-0.8014
|
-0.4083
|
0.4572
|
0.8958
0.7383 |
0.7274 |
0.7524 |
0.7984 |
0.7444 |
0.7694 |
0.8779 |
0.9708 |
0.7555 |
0.7430 |
0.7960 |
0.9463 |
0.8276 |
0.7261 |
0.8090 |
0.7235 |
0.7235 |
0.7328 |
0.7964 |
0.8493 |
331
1 Examinee892
1.00 TEST0001
1 Examinee893
1.00 TEST0001
1 Examinee894
1.00 TEST0001
1 Examinee895
1.00 TEST0001
1 Examinee896
1.00 TEST0001
1 Examinee897
1.00 TEST0001
1 Examinee898
1.00 TEST0001
1 Examinee899
1.00 TEST0001
1 Examinee900
1.00 TEST0001
1 Examinee901
1.00 TEST0001
1 Examinee902
1.00 TEST0001
1 Examinee903
1.00 TEST0001
1 Examinee904
1.00 TEST0001
1 Examinee905
1.00 TEST0001
1 Examinee906
1.00 TEST0001
1 Examinee907
1.00 TEST0001
1 Examinee908
1.00 TEST0001
1 Examinee909
1.00 TEST0001
1 Examinee910
1.00 TEST0001
1 Examinee911
1.00 TEST0001
25
7
25
13
25
10
25
12
25
9
25
14
25
13
25
11
25
7
25
8
25
3
25
8
25
13
25
10
25
11
25
10
25
13
25
14
25
10
25
13
|
28.00 |
|
52.00 |
|
40.00 |
|
48.00 |
|
36.00 |
|
56.00 |
|
52.00 |
|
44.00 |
|
28.00 |
|
32.00 |
|
12.00 |
|
32.00 |
|
52.00 |
|
40.00 |
|
44.00 |
|
40.00 |
|
52.00 |
|
56.00 |
|
40.00 |
|
52.00 |
|
-1.4591 0.7450 |
|
0.9276 0.8537 |
|
-0.3940 0.7334 |
|
0.3510 0.7856 |
|
-0.2923 0.7381 |
|
1.6188 0.9684 |
|
1.3791 0.9245 |
|
-0.6321 0.7258 |
|
-0.7960 0.7235 |
|
-0.7897 0.7236 |
|
-4.0000 999.0000 |
|
-1.0385 0.7253 |
|
0.9276 0.8537 |
|
-0.4042 0.7330 |
|
0.3358 0.7842 |
|
-0.2971 0.7379 |
|
1.4758 0.9417 |
|
2.2136 1.0953 |
|
-0.1783 0.7443 |
|
-0.2818 0.7387 |
332
1 Examinee912
1.00 TEST0001
1 Examinee913
1.00 TEST0001
1 Examinee914
1.00 TEST0001
1 Examinee915
1.00 TEST0001
1 Examinee916
1.00 TEST0001
1 Examinee917
1.00 TEST0001
1 Examinee918
1.00 TEST0001
1 Examinee919
1.00 TEST0001
1 Examinee920
1.00 TEST0001
1 Examinee921
1.00 TEST0001
1 Examinee922
1.00 TEST0001
1 Examinee923
1.00 TEST0001
1 Examinee924
1.00 TEST0001
1 Examinee925
1.00 TEST0001
1 Examinee926
1.00 TEST0001
1 Examinee927
1.00 TEST0001
1 Examinee928
1.00 TEST0001
1 Examinee929
1.00 TEST0001
1 Examinee930
1.00 TEST0001
1 Examinee931
1.00 TEST0001
25
15
25
16
25
11
25
13
25
13
25
3
25
7
25
11
25
13
25
6
25
9
25
8
25
6
25
15
25
15
25
10
25
8
25
9
25
6
25
9
|
60.00 |
|
64.00 |
|
44.00 |
|
52.00 |
|
52.00 |
|
12.00 |
|
28.00 |
|
44.00 |
|
52.00 |
|
24.00 |
|
36.00 |
|
32.00 |
|
24.00 |
|
60.00 |
|
60.00 |
|
40.00 |
|
32.00 |
|
36.00 |
|
24.00 |
|
36.00 |
|
1.2296
|
3.5439
|
0.3821
|
1.0672
|
1.0077
|
-2.5805
|
-1.2575
|
0.1988
|
-0.1239
|
-2.0169
|
-0.3741
|
-1.5296
|
-1.1377
|
1.3672
|
1.4897
|
0.1604
|
-0.5317
|
-1.1552
|
-1.0059
|
-1.7466
0.8993 |
1.4444 |
0.7887 |
0.8739 |
0.8651 |
0.9216 |
0.7327 |
0.7717 |
0.7476 |
0.8095 |
0.7343 |
0.7507 |
0.7279 |
0.9224 |
0.9442 |
0.7685 |
0.7284 |
0.7285 |
0.7247 |
0.7725 |
333
1 Examinee932
1.00 TEST0001
1 Examinee933
1.00 TEST0001
1 Examinee934
1.00 TEST0001
1 Examinee935
1.00 TEST0001
1 Examinee936
1.00 TEST0001
1 Examinee937
1.00 TEST0001
1 Examinee938
1.00 TEST0001
1 Examinee939
1.00 TEST0001
1 Examinee940
1.00 TEST0001
1 Examinee941
1.00 TEST0001
1 Examinee942
1.00 TEST0001
1 Examinee943
1.00 TEST0001
1 Examinee944
1.00 TEST0001
1 Examinee945
1.00 TEST0001
1 Examinee946
1.00 TEST0001
1 Examinee947
1.00 TEST0001
1 Examinee948
1.00 TEST0001
1 Examinee949
1.00 TEST0001
1 Examinee950
1.00 TEST0001
1 Examinee951
1.00 TEST0001
25
17
25
13
25
9
25
12
25
12
25
11
25
8
25
10
25
7
25
16
25
13
25
15
25
12
25
9
25
11
25
15
25
12
25
4
25
14
25
8
|
68.00 |
|
52.00 |
|
36.00 |
|
48.00 |
|
48.00 |
|
44.00 |
|
32.00 |
|
40.00 |
|
28.00 |
|
64.00 |
|
52.00 |
|
60.00 |
|
48.00 |
|
36.00 |
|
44.00 |
|
60.00 |
|
48.00 |
|
16.00 |
|
56.00 |
|
32.00 |
|
1.6296
|
1.4227
|
0.6667
|
0.4317
|
0.2107
|
-0.0402
|
-0.5107
|
-0.3018
|
-1.6266
|
2.9139
|
0.6739
|
1.2107
|
1.3757
|
-0.8376
|
0.6447
|
1.1715
|
0.8417
|
-1.6088
|
2.3189
|
-0.7966
0.9705 |
0.9322 |
0.8199 |
0.7937 |
0.7727 |
0.7532 |
0.7291 |
0.7377 |
0.7596 |
1.2715 |
0.8207 |
0.8963 |
0.9239 |
0.7234 |
0.8173 |
0.8900 |
0.8420 |
0.7578 |
1.1202 |
0.7235 |
334
1 Examinee952
1.00 TEST0001
1 Examinee953
1.00 TEST0001
1 Examinee954
1.00 TEST0001
1 Examinee955
1.00 TEST0001
1 Examinee956
1.00 TEST0001
1 Examinee957
1.00 TEST0001
1 Examinee958
1.00 TEST0001
1 Examinee959
1.00 TEST0001
1 Examinee960
1.00 TEST0001
1 Examinee961
1.00 TEST0001
1 Examinee962
1.00 TEST0001
1 Examinee963
1.00 TEST0001
1 Examinee964
1.00 TEST0001
1 Examinee965
1.00 TEST0001
1 Examinee966
1.00 TEST0001
1 Examinee967
1.00 TEST0001
1 Examinee968
1.00 TEST0001
1 Examinee969
1.00 TEST0001
1 Examinee970
1.00 TEST0001
1 Examinee971
1.00 TEST0001
25
14
25
14
25
13
25
10
25
12
25
13
25
6
25
9
25
6
25
8
25
16
25
7
25
6
25
12
25
13
25
13
25
10
25
12
25
13
25
10
|
56.00 |
|
56.00 |
|
52.00 |
|
40.00 |
|
48.00 |
|
52.00 |
|
24.00 |
|
36.00 |
|
24.00 |
|
32.00 |
|
64.00 |
|
28.00 |
|
24.00 |
|
48.00 |
|
52.00 |
|
52.00 |
|
40.00 |
|
48.00 |
|
52.00 |
|
40.00 |
|
1.1182
|
1.6602
|
1.2142
|
-1.1072
|
0.8432
|
0.8765
|
-1.1222
|
0.0916
|
-1.1824
|
-0.6802
|
1.5577
|
-0.9009
|
-2.8083
|
-0.2835
|
1.0540
|
0.7994
|
-0.3096
|
0.8457
|
0.6234
|
0.5485
0.8817 |
0.9764 |
0.8968 |
0.7270 |
0.8422 |
0.8467 |
0.7274 |
0.7629 |
0.7295 |
0.7249 |
0.9568 |
0.7235 |
0.9796 |
0.7386 |
0.8720 |
0.8364 |
0.7373 |
0.8425 |
0.8147 |
0.8062 |
335
1 Examinee972
1.00 TEST0001
1 Examinee973
1.00 TEST0001
1 Examinee974
1.00 TEST0001
1 Examinee975
1.00 TEST0001
1 Examinee976
1.00 TEST0001
1 Examinee977
1.00 TEST0001
1 Examinee978
1.00 TEST0001
1 Examinee979
1.00 TEST0001
1 Examinee980
1.00 TEST0001
1 Examinee981
1.00 TEST0001
1 Examinee982
1.00 TEST0001
1 Examinee983
1.00 TEST0001
1 Examinee984
1.00 TEST0001
1 Examinee985
1.00 TEST0001
1 Examinee986
1.00 TEST0001
1 Examinee987
1.00 TEST0001
1 Examinee988
1.00 TEST0001
1 Examinee989
1.00 TEST0001
1 Examinee990
1.00 TEST0001
1 Examinee991
1.00 TEST0001
25
10
25
10
25
10
25
10
25
9
25
10
25
11
25
11
25
10
25
9
25
9
25
10
25
8
25
11
25
14
25
10
25
13
25
12
25
8
25
16
|
40.00 |
|
40.00 |
|
40.00 |
|
40.00 |
|
36.00 |
|
40.00 |
|
44.00 |
|
44.00 |
|
40.00 |
|
36.00 |
|
36.00 |
|
40.00 |
|
32.00 |
|
44.00 |
|
56.00 |
|
40.00 |
|
52.00 |
|
48.00 |
|
32.00 |
|
64.00 |
|
0.2510
|
-0.4586
|
-0.7187
|
-0.0947
|
0.1864
|
0.4598
|
0.1427
|
-0.1456
|
-0.0716
|
-0.6283
|
-0.9073
|
0.0337
|
-0.3268
|
1.1594
|
1.0251
|
-0.4141
|
1.0476
|
0.3478
|
-1.0070
|
1.8300
0.7763 |
0.7309 |
0.7243 |
0.7495 |
0.7707 |
0.7966 |
0.7670 |
0.7463 |
0.7510 |
0.7259 |
0.7235 |
0.7585 |
0.7364 |
0.8881 |
0.8677 |
0.7326 |
0.8710 |
0.7853 |
0.7247 |
1.0106 |
336
1 Examinee992
|
|
1.00 TEST0001 25 13 52.00 | 0.5020 0.8011 |
1 Examinee993
|
|
1.00 TEST0001 25
7 28.00 | -0.7761 0.7237 |
1 Examinee994
|
|
1.00 TEST0001 25 14 56.00 | 0.7304 0.8277 |
1 Examinee995
|
|
1.00 TEST0001 25 14 56.00 | 1.0354 0.8692 |
1 Examinee996
|
|
1.00 TEST0001 25 14 56.00 | 1.0770 0.8754 |
1 Examinee997
|
|
1.00 TEST0001 25 12 48.00 | 0.8216 0.8393 |
1 Examinee998
|
|
1.00 TEST0001 25
9 36.00 | -0.8840 0.7234 |
1 Examinee999
|
|
1.00 TEST0001 25 16 64.00 | 2.2421 1.1020 |
----------------------------------------------------------------
======================================
TEST0001
TEST0001
1.0000
TEST:
TEST0001
MEAN:
0.0273
S.D.:
1.3074
VARIANCE:
1.7093
337
ESTIMATES
TEST:
TEST0001
RMS:
0.8058
VARIANCE:
0.6492
EMPIRICAL
RELIABILITY:
0.6202
IN PHASE-3
IN PHASE-3
PH1
1
BILOG-MG V3.0
REV 19990104.1300
MODEL
DISTRIBUTED BY
CHICAGO, IL 60646
(800) 247-6113
(847) 675-0720
338
1
*** PHASE 1 ***
sample 25 by 999
NPArm = 3,
LOGistic,
SAVe;
===============================
CF.DAT
IF.DAT
339
CASE WEIGHTING
SF.DAT
NONE EMPLOYED
ITEM RESPONSE MODEL
>SAVE MASter = 'RG.MAS',
CALib = 'RG.CAL',
PARm = 'RG.PAR',
SCOre = 'RG.SCO',
COVariance = 'RG.COV',
TSTat = 'RG.TST',
ISTat = 'RG.IST';
BILOG-MG SAVE FILES
[OUTPUT FILES]
BILOG-MG MASTER BINARY DATA RG.MAS
CALIBRATION BINARY DATA FILERG.CAL
CLASSICAL ITEM STATISTICS RG.IST
RG.PAR
RG.SCO
ESTIMATED COVARIANCE FILE RG.COV
RG.TST
340
==========================
MAIN TEST LENGTHS:
25
>INPUT NTOtal = 25,
NALt = 3,
NIDchar = 11;
=========================
1
25
3
11
NUMBER OF GROUPS
1
1
TYPE OF DATA
341
>ITEMS ;
TEST SPECIFICATIONS
===================
INUmber = (1(1)25);
NUMBER OF ITEMS: 25
ITEM ITEM
ITEM ITEM
ITEM ITEM
ITEM ITEM
NUMBER NAME
NUMBER
NAME
----------------------------------------------------------------------1 ITEM0001
9 ITEM0009
17 ITEM0017 25 ITEM0025
2 ITEM0002 10 ITEM0010 18 ITEM0018
3 ITEM0003 11 ITEM0011 19 ITEM0019
4 ITEM0004 12 ITEM0012 20 ITEM0020
5 ITEM0005 13 ITEM0013 21 ITEM0021
6 ITEM0006 14 ITEM0014 22 ITEM0022
7 ITEM0007 15 ITEM0015 23 ITEM0023
8 ITEM0008 16 ITEM0016 24 ITEM0024
-----------------------------------------------------------------------
FORM SPECIFICATIONS
342
===================
(11A1, 25A1)
OBSERVATION #
1 WEIGHT:
GROUP #: 1
TRIED RIGHT
25.000 7.000
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 0.0 0.0 1.0 1.0 0.0 1.0 1.0 1.0 0.0 0.0
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0
ITEM 21 22 23 24 25
TRIED 1.0 1.0 1.0 1.0 1.0
RIGHT 0.0 0.0 0.0 0.0 0.0
OBSERVATION #
2 WEIGHT:
343
GROUP #: 1
TRIED RIGHT
25.000 11.000
ITEM
1 2 3 4 5 6 7 8 9 10
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 0.0 1.0 1.0 0.0 1.0 1.0 0.0 1.0
ITEM 11 12 13 14 15 16 17 18 19 20
TRIED 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 0.0
ITEM 21 22 23 24 25
TRIED 1.0 1.0 1.0 1.0 1.0
RIGHT 1.0 0.0 0.0 0.0 1.0
999 OBSERVATIONS WRITTEN TO FILE: RG.MAS
ITEM NAME
#TRIED #RIGHT PCT
------------------------------------------------------------------------1 ITEM0001 999.0 694.0 69.5 -0.82 0.246 0.324
2 ITEM0002 999.0 477.0 47.7 0.09 0.155 0.194
3 ITEM0003 999.0 579.0 58.0 -0.32 0.237 0.300
4 ITEM0004 999.0 571.0 57.2 -0.29 0.218 0.275
5 ITEM0005 999.0 461.0 46.1 0.15 0.159 0.199
344
6 ITEM0006 999.0 801.0 80.2 -1.40 0.266 0.380
7 ITEM0007 999.0 516.0 51.7 -0.07 0.236 0.295
8 ITEM0008 999.0 703.0 70.4 -0.86 0.219 0.289
9 ITEM0009 999.0 390.0 39.0 0.45 0.225 0.286
10 ITEM0010 999.0 560.0 56.1 -0.24 0.268 0.338
11 ITEM0011 999.0 264.0 26.4 1.02 0.022 0.030
12 ITEM0012 999.0 511.0 51.2 -0.05 0.256 0.321
13 ITEM0013 999.0 500.0 50.1 0.00 0.092 0.115
14 ITEM0014 999.0 743.0 74.4 -1.07 0.200 0.271
15 ITEM0015 999.0 195.0 19.5 1.42 0.091 0.130
16 ITEM0016 999.0 210.0 21.0 1.32 0.071 0.100
17 ITEM0017 999.0 281.0 28.1 0.94 0.047 0.062
18 ITEM0018 999.0 401.0 40.1 0.40 0.101 0.129
19 ITEM0019 999.0 284.0 28.4 0.92 0.128 0.170
20 ITEM0020 999.0 271.0 27.1 0.99 0.031 0.042
21 ITEM0021 999.0 290.0 29.0 0.89 0.108 0.144
22 ITEM0022 999.0 374.0 37.4 0.51 0.173 0.221
23 ITEM0023 999.0 198.0 19.8 1.40 0.043 0.061
24 ITEM0024 999.0 251.0 25.1 1.09 0.068 0.093
25 ITEM0025 999.0 187.0 18.7 1.47 0.069 0.100
-------------------------------------------------------------------------
IN PHASE-1
IN PHASE-1
11/29/2011 14:55:24
PH2
1
BILOG-MG V3.0
REV 19990329.1300
345
MODEL
*** PHASE 2 ***
sample 25 by 999
TPRior,
GPRior,
FLOat;
======================
20
0.0100
1.0000
2
NO
DATA HANDLING:
CONSTRAINT DISTRIBUTION ON ASYMPTOTES: YES
346
YES
PROGRAM DEFAULTS
1
--------------------------------------------------------------------------------
******************************
TEST0001
******************************
METHOD OF SOLUTION:
1
2
3
4
5
POINT -0.4000E+01 -0.3429E+01 -0.2857E+01 -0.2286E+01 -0.1714E+01
WEIGHT 0.7648E-04 0.6387E-03 0.3848E-02 0.1673E-01 0.5245E-01
6
7
8
9
10
POINT -0.1143E+01 -0.5714E+00 -0.8882E-15 0.5714E+00 0.1143E+01
WEIGHT 0.1186E+00 0.1936E+00 0.2280E+00 0.1936E+00 0.1186E+00
347
11
12
13
14
15
POINT 0.1714E+01 0.2286E+01 0.2857E+01 0.3429E+01 0.4000E+01
WEIGHT 0.5245E-01 0.1673E-01 0.3848E-02 0.6387E-03 0.7648E-04
THRESHOLDS
SLOPES
ASYMPTOTES
ITEM
BETA
---------------------------------------------------------------------ITEM0001 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0002 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0003 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0004 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0005 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0006 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0007 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0008 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0009 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0010 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0011 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0012 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0013 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0014 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0015 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0016 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0017 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0018 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0019 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0020 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0021 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0022 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0023 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0024 0.000 2.000 1.000 1.649
7.67 14.33
ITEM0025 0.000 2.000 1.000 1.649
7.67 14.33
----------------------------------------------------------------------
348
[E-M CYCLES]
-2 LOG LIKELIHOOD =
CYCLE
31138.675
-2 LOG LIKELIHOOD =
30072.228
UPDATED PRIOR ON ASYMPTOTES; ALPHA & BETA = 5.50451 16.49549
-0.44832 0.50000
2.52821 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30024.721
-0.40636 0.50000
2.28999 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30009.892
-0.38788 0.50000
349
CYCLE
2.15727
2.00000
-2 LOG LIKELIHOOD =
30007.423
-0.37098 0.50000
2.01604 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30002.319
-0.36372 0.50000
1.98178 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30003.215
-0.36865 0.50000
1.94561 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30000.695
350
-0.37494 0.50000
1.93545 2.00000
CYCLE
-2 LOG LIKELIHOOD =
29998.985
-0.38060 0.50000
1.97164 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30002.404
-0.39422 0.50000
1.94835 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30000.469
-0.40239 0.50000
1.96612 2.00000
351
CYCLE
-2 LOG LIKELIHOOD =
29999.904
-0.41031 0.50000
1.98310 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30000.656
-0.41953 0.50000
1.98170 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30001.560
-0.42843 0.50000
1.97228 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30000.565
UPDATED PRIOR ON ASYMPTOTES; ALPHA & BETA =
3.71523 18.28477
352
CYCLE
-0.43633 0.50000
2.00134 2.00000
-2 LOG LIKELIHOOD =
30002.558
-0.44497 0.50000
1.97563 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30002.523
-0.45614 0.50000
1.99080 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30002.366
-0.46753 0.50000
2.02269 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30005.187
353
-0.48069 0.50000
2.00783 2.00000
CYCLE
-2 LOG LIKELIHOOD =
30005.521
-0.49547 0.50000
2.01135 2.00000
CYCLE
====> NOTE: CONVERGENCE HAS NOT BEEN REACHED TO CRITERION =
0.01000
[NEWTON CYCLES]
-0.50747 0.50000
2.06556 2.00000
354
-2 LOG LIKELIHOOD:
30003.2350
-0.51748 0.50000
2.04068 2.00000
-2 LOG LIKELIHOOD:
30004.3749
====> NOTE: CONVERGENCE HAS NOT BEEN REACHED TO CRITERION =
0.01000
---------------------------------------------------------------------------27. 43. 61. 144. 201. 235. 149. 96. 43.
----------------------------------------------------------------------------2.411 -1.938 -1.328 -0.762 -0.262 0.265 0.798 1.288 2.024
---------------------------------------------------------------------------1
ITEM
CHISQ
DF
S.E.
S.E.
S.E.
S.E.
S.E. (PROB)
------------------------------------------------------------------------------355
ITEM0001 | 0.749 | 0.829 | -0.904 | 0.638 | 0.107 | 31.8
| 0.143* | 0.133* | 0.238* | 0.102* | 0.065* | (0.0001)
|
|
|
|
|
|
ITEM0002 | -0.484 | 0.605 | 0.800 | 0.518 | 0.141 | 14.1
| 0.264* | 0.139* | 0.354* | 0.119* | 0.075* | (0.1191)
|
|
|
|
|
|
ITEM0003 | 0.154 | 0.770 | -0.200 | 0.610 | 0.097 | 16.0
| 0.155* | 0.125* | 0.215* | 0.099* | 0.059* | (0.0667)
|
|
|
|
|
|
ITEM0004 | 0.047 | 0.775 | -0.061 | 0.613 | 0.123 | 16.2
| 0.194* | 0.137* | 0.256* | 0.108* | 0.070* | (0.0636)
|
|
|
|
|
|
ITEM0005 | -0.614 | 0.539 | 1.139 | 0.475 | 0.157 | 13.0
| 0.296* | 0.135* | 0.431* | 0.119* | 0.078* | (0.1618)
|
|
|
|
|
|
ITEM0006 | 1.731 | 1.377 | -1.257 | 0.809 | 0.080 | 32.5
| 0.144* | 0.177* | 0.152* | 0.104* | 0.050* | (0.0000)
|
|
|
|
|
|
ITEM0007 | -0.121 | 0.979 | 0.123 | 0.699 | 0.079 | 23.3
| 0.154* | 0.152* | 0.149* | 0.108* | 0.047* | (0.0030)
|
|
|
|
|
|
ITEM0008 | 0.887 | 1.014 | -0.875 | 0.712 | 0.087 | 28.5
| 0.127* | 0.140* | 0.176* | 0.099* | 0.054* | (0.0002)
|
|
|
|
|
|
ITEM0009 | -0.760 | 0.985 | 0.772 | 0.702 | 0.067 | 24.7
| 0.189* | 0.172* | 0.145* | 0.122* | 0.040* | (0.0018)
|
|
|
|
|
|
ITEM0010 | 0.081 | 0.913 | -0.089 | 0.674 | 0.089 | 22.9
| 0.154* | 0.140* | 0.174* | 0.103* | 0.054* | (0.0065)
|
|
|
|
|
|
ITEM0011 | -1.544 | 0.307 | 5.033 | 0.293 | 0.105 | 10.4
| 0.321* | 0.096* | 1.543* | 0.092* | 0.049* | (0.3215)
|
|
|
|
|
|
ITEM0012 | -0.141 | 0.917 | 0.154 | 0.676 | 0.078 | 29.7
| 0.152* | 0.148* | 0.156* | 0.109* | 0.047* | (0.0005)
|
|
|
|
|
|
ITEM0013 | -0.489 | 0.407 | 1.203 | 0.377 | 0.186 | 15.4
| 0.301* | 0.108* | 0.642* | 0.100* | 0.087* | (0.0799)
|
|
|
|
|
|
ITEM0014 | 0.977 | 0.677 | -1.443 | 0.561 | 0.118 | 15.2
8.0
9.0
9.0
9.0
9.0
7.0
8.0
7.0
8.0
9.0
9.0
9.0
9.0
8.0
356
| 0.144* | 0.110* | 0.325* | 0.091* | 0.071* | (0.0554)
|
|
|
|
|
|
ITEM0015 | -2.195 | 0.494 | 4.440 | 0.443 | 0.098 | 4.8
| 0.455* | 0.177* | 1.220* | 0.158* | 0.039* | (0.8502)
|
|
|
|
|
|
ITEM0016 | -1.903 | 0.345 | 5.514 | 0.326 | 0.090 | 1.7
| 0.358* | 0.113* | 1.675* | 0.107* | 0.041* | (0.9955)
|
|
|
|
|
|
ITEM0017 | -1.464 | 0.304 | 4.808 | 0.291 | 0.113 | 3.6
| 0.321* | 0.095* | 1.479* | 0.091* | 0.052* | (0.9337)
|
|
|
|
|
|
ITEM0018 | -0.822 | 0.324 | 2.534 | 0.309 | 0.133 | 6.5
| 0.269* | 0.090* | 0.852* | 0.086* | 0.067* | (0.6898)
|
|
|
|
|
|
ITEM0019 | -2.131 | 0.648 | 3.291 | 0.544 | 0.184 | 9.2
| 0.590* | 0.260* | 0.828* | 0.218* | 0.048* | (0.4169)
|
|
|
|
|
|
ITEM0020 | -1.473 | 0.254 | 5.805 | 0.246 | 0.105 | 12.9
| 0.297* | 0.078* | 1.857* | 0.076* | 0.048* | (0.1692)
|
|
|
|
|
|
ITEM0021 | -2.795 | 0.973 | 2.872 | 0.697 | 0.225 | 16.1
| 0.894* | 0.472* | 0.718* | 0.338* | 0.037* | (0.0654)
|
|
|
|
|
|
ITEM0022 | -1.007 | 0.550 | 1.832 | 0.482 | 0.130 | 6.1
| 0.318* | 0.148* | 0.445* | 0.130* | 0.066* | (0.6410)
|
|
|
|
|
|
ITEM0023 | -2.226 | 0.364 | 6.116 | 0.342 | 0.110 | 11.9
| 0.443* | 0.127* | 1.943* | 0.120* | 0.038* | (0.2211)
|
|
|
|
|
|
ITEM0024 | -1.941 | 0.411 | 4.718 | 0.380 | 0.138 | 4.9
| 0.451* | 0.144* | 1.392* | 0.133* | 0.048* | (0.8390)
|
|
|
|
|
|
ITEM0025 | -2.181 | 0.382 | 5.715 | 0.357 | 0.093 | 12.3
| 0.418* | 0.131* | 1.752* | 0.123* | 0.038* | (0.1982)
------------------------------------------------------------------------------* STANDARD ERROR
9.0
9.0
9.0
9.0
9.0
9.0
9.0
8.0
9.0
9.0
9.0
LARGEST CHANGE =
0.053243
383.4 216.0
(0.0000)
------------------------------------------------------------------------------357
PARAMETER
MEAN STN DEV
----------------------------------ASYMPTOTE 0.117 0.038
SLOPE
0.646 0.296
LOG(SLOPE) -0.542 0.475
1
2
3
4
5
POINT
-0.4058E+01 -0.3478E+01 -0.2899E+01 -0.2319E+01 -0.1739E+01
POSTERIOR 0.1219E-03 0.9495E-03 0.5112E-02 0.1899E-01 0.5104E-01
6
7
8
9
10
POINT
-0.1159E+01 -0.5790E+00 0.9339E-03 0.5808E+00 0.1161E+01
POSTERIOR 0.1102E+00 0.1906E+00 0.2358E+00 0.1997E+00 0.1177E+00
11
12
13
14
15
POINT
0.1741E+01 0.2321E+01 0.2900E+01 0.3480E+01 0.4060E+01
POSTERIOR 0.4955E-01 0.1549E-01 0.3834E-02 0.7817E-03 0.1276E-03
MEAN
S.D.
0.00000
1.00000
IN PHASE-2
IN PHASE-2
11/29/2011 14:55:25
358
PH3
1
BILOG-MG V3.0
MODEL
*** PHASE 3 ***
sample 25 by 999
>SCORE METhod = 1;
INFORMATION
MAXIMUM LIKELIHOOD
RG.SCO
RG.PH3
TYPE OF RESCALING:
----------------------1
NONE REQUESTED
NONE REQUESTED
NONE REQUESTED
359
******************************
SCORING
******************************
1
---------------------------------------------------------------1 Examinee001
|
|
1.00 TEST0001 25
7 28.00 | -0.8475 0.7581 |
1 Examinee002
|
|
1.00 TEST0001 25 11 44.00 | -0.6235 0.7445 |
1 Examinee003
|
|
1.00 TEST0001 25 11 44.00 | 0.4690 0.7535 |
1 Examinee004
|
|
1.00 TEST0001 25 12 48.00 | 0.2823 0.7450 |
1 Examinee005
|
|
1.00 TEST0001 25 10 40.00 | -0.0223 0.7367 |
1 Examinee006
|
|
1.00 TEST0001 25
9 36.00 | -0.0618 0.7362 |
1 Examinee007
|
|
1.00 TEST0001 25 10 40.00 | -0.2247 0.7354 |
1 Examinee008
|
|
1.00 TEST0001 25 11 44.00 | 0.1946 0.7418 |
1 Examinee009
|
|
1.00 TEST0001 25 14 56.00 | 1.0642 0.7970 |
1 Examinee010
|
|
1.00 TEST0001 25
9 36.00 | -0.1127 0.7357 |
1 Examinee011
|
|
1.00 TEST0001 25 12 48.00 | 0.2394 0.7433 |
1 Examinee012
|
|
1.00 TEST0001 25 13 52.00 | 1.3258 0.8228 |
1 Examinee013
|
|
1.00 TEST0001 25 16 64.00 | 1.8460 0.8822 |
1 Examinee014
|
|
1.00 TEST0001 25 15 60.00 | 2.1006 0.9135 |
S.E.
360
1 Examinee015
1.00 TEST0001
1 Examinee016
1.00 TEST0001
1 Examinee017
1.00 TEST0001
1 Examinee018
1.00 TEST0001
1 Examinee019
1.00 TEST0001
1 Examinee020
1.00 TEST0001
1 Examinee021
1.00 TEST0001
1 Examinee022
1.00 TEST0001
1 Examinee023
1.00 TEST0001
1 Examinee024
1.00 TEST0001
1 Examinee025
1.00 TEST0001
1 Examinee026
1.00 TEST0001
1 Examinee027
1.00 TEST0001
1 Examinee028
1.00 TEST0001
1 Examinee029
1.00 TEST0001
1 Examinee030
1.00 TEST0001
1 Examinee031
1.00 TEST0001
1 Examinee032
1.00 TEST0001
1 Examinee033
1.00 TEST0001
1 Examinee034
1.00 TEST0001
25
10
25
13
25
16
25
8
25
5
25
12
25
11
25
11
25
14
25
13
25
7
25
10
25
15
25
10
25
13
25
16
25
16
25
13
25
11
25
18
|
40.00 |
|
52.00 |
|
64.00 |
|
32.00 |
|
20.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
56.00 |
|
52.00 |
|
28.00 |
|
40.00 |
|
60.00 |
|
40.00 |
|
52.00 |
|
64.00 |
|
64.00 |
|
52.00 |
|
44.00 |
|
72.00 |
|
0.4011
|
1.8065
|
1.3476
|
-0.8184
|
-2.3037
|
0.9782
|
0.3532
|
-0.0557
|
0.9054
|
0.5501
|
-0.8194
|
-0.0640
|
1.6010
|
-0.5835
|
0.9541
|
2.0950
|
2.5156
|
-0.1141
|
0.1326
|
3.7707
0.7501 |
0.8775 |
0.8251 |
0.7559 |
1.1322 |
0.7893 |
0.7479 |
0.7362 |
0.7831 |
0.7580 |
0.7560 |
0.7361 |
0.8532 |
0.7428 |
0.7872 |
0.9128 |
0.9659 |
0.7357 |
0.7400 |
1.1461 |
361
1 Examinee035
1.00 TEST0001
1 Examinee036
1.00 TEST0001
1 Examinee037
1.00 TEST0001
1 Examinee038
1.00 TEST0001
1 Examinee039
1.00 TEST0001
1 Examinee040
1.00 TEST0001
1 Examinee041
1.00 TEST0001
1 Examinee042
1.00 TEST0001
1 Examinee043
1.00 TEST0001
1 Examinee044
1.00 TEST0001
1 Examinee045
1.00 TEST0001
1 Examinee046
1.00 TEST0001
1 Examinee047
1.00 TEST0001
1 Examinee048
1.00 TEST0001
1 Examinee049
1.00 TEST0001
1 Examinee050
1.00 TEST0001
1 Examinee051
1.00 TEST0001
1 Examinee052
1.00 TEST0001
1 Examinee053
1.00 TEST0001
1 Examinee054
1.00 TEST0001
25
12
25
8
25
10
25
14
25
10
25
14
25
13
25
7
25
13
25
11
25
11
25
13
25
8
25
11
25
13
25
13
25
9
25
13
25
11
25
9
|
48.00 |
|
32.00 |
|
40.00 |
|
56.00 |
|
40.00 |
|
56.00 |
|
52.00 |
|
28.00 |
|
52.00 |
|
44.00 |
|
44.00 |
|
52.00 |
|
32.00 |
|
44.00 |
|
52.00 |
|
52.00 |
|
36.00 |
|
52.00 |
|
44.00 |
|
36.00 |
|
0.6384
|
-0.3336
|
-0.1418
|
1.1875
|
-0.5540
|
1.9981
|
1.5587
|
-1.9122
|
0.3239
|
0.4533
|
0.2608
|
1.4055
|
-1.3823
|
0.4294
|
1.3482
|
1.1171
|
-0.2947
|
0.0404
|
0.5803
|
-0.5181
0.7635 |
0.7362 |
0.7355 |
0.8087 |
0.7416 |
0.9008 |
0.8484 |
0.9653 |
0.7466 |
0.7527 |
0.7441 |
0.8313 |
0.8261 |
0.7515 |
0.8252 |
0.8019 |
0.7358 |
0.7378 |
0.7598 |
0.7404 |
362
1 Examinee055
1.00 TEST0001
1 Examinee056
1.00 TEST0001
1 Examinee057
1.00 TEST0001
1 Examinee058
1.00 TEST0001
1 Examinee059
1.00 TEST0001
1 Examinee060
1.00 TEST0001
1 Examinee061
1.00 TEST0001
1 Examinee062
1.00 TEST0001
1 Examinee063
1.00 TEST0001
1 Examinee064
1.00 TEST0001
1 Examinee065
1.00 TEST0001
1 Examinee066
1.00 TEST0001
1 Examinee067
1.00 TEST0001
1 Examinee068
1.00 TEST0001
1 Examinee069
1.00 TEST0001
1 Examinee070
1.00 TEST0001
1 Examinee071
1.00 TEST0001
1 Examinee072
1.00 TEST0001
1 Examinee073
1.00 TEST0001
1 Examinee074
1.00 TEST0001
25
8
25
13
25
16
25
16
25
8
25
10
25
11
25
8
25
13
25
12
25
11
25
13
25
13
25
13
25
9
25
15
25
11
25
16
25
13
25
13
|
32.00 |
|
52.00 |
|
64.00 |
|
64.00 |
|
32.00 |
|
40.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
48.00 |
|
44.00 |
|
52.00 |
|
52.00 |
|
52.00 |
|
36.00 |
|
60.00 |
|
44.00 |
|
64.00 |
|
52.00 |
|
52.00 |
|
-0.7480
|
0.9714
|
2.8121
|
1.9357
|
-1.1460
|
-0.8846
|
-0.2077
|
-0.9158
|
0.3689
|
0.4255
|
0.3741
|
0.2793
|
1.5420
|
0.7521
|
-1.0253
|
1.2629
|
-0.2172
|
1.9727
|
0.4567
|
-0.2782
0.7512 |
0.7887 |
1.0045 |
0.8932 |
0.7888 |
0.7611 |
0.7354 |
0.7637 |
0.7486 |
0.7513 |
0.7488 |
0.7448 |
0.8465 |
0.7713 |
0.7744 |
0.8163 |
0.7354 |
0.8977 |
0.7529 |
0.7357 |
363
1 Examinee075
1.00 TEST0001
1 Examinee076
1.00 TEST0001
1 Examinee077
1.00 TEST0001
1 Examinee078
1.00 TEST0001
1 Examinee079
1.00 TEST0001
1 Examinee080
1.00 TEST0001
1 Examinee081
1.00 TEST0001
1 Examinee082
1.00 TEST0001
1 Examinee083
1.00 TEST0001
1 Examinee084
1.00 TEST0001
1 Examinee085
1.00 TEST0001
1 Examinee086
1.00 TEST0001
1 Examinee087
1.00 TEST0001
1 Examinee088
1.00 TEST0001
1 Examinee089
1.00 TEST0001
1 Examinee090
1.00 TEST0001
1 Examinee091
1.00 TEST0001
1 Examinee092
1.00 TEST0001
1 Examinee093
1.00 TEST0001
1 Examinee094
1.00 TEST0001
25
16
25
18
25
15
25
7
25
14
25
17
25
16
25
8
25
11
25
10
25
11
25
14
25
13
25
11
25
10
25
13
25
12
25
10
25
13
25
8
|
64.00 |
|
72.00 |
|
60.00 |
|
28.00 |
|
56.00 |
|
68.00 |
|
64.00 |
|
32.00 |
|
44.00 |
|
40.00 |
|
44.00 |
|
56.00 |
|
52.00 |
|
44.00 |
|
40.00 |
|
52.00 |
|
48.00 |
|
40.00 |
|
52.00 |
|
32.00 |
|
1.6639
|
3.1678
|
0.8686
|
-1.3473
|
1.3518
|
2.9530
|
2.1257
|
-0.8800
|
-0.0777
|
-0.2839
|
-0.6419
|
0.5245
|
0.7245
|
-0.7277
|
-0.3241
|
1.6508
|
0.9458
|
-0.2020
|
0.6231
|
-0.4454
0.8605 |
1.0532 |
0.7802 |
0.8198 |
0.8256 |
1.0234 |
0.9167 |
0.7607 |
0.7360 |
0.7357 |
0.7454 |
0.7566 |
0.7693 |
0.7499 |
0.7361 |
0.8590 |
0.7865 |
0.7354 |
0.7625 |
0.7383 |
364
1 Examinee095
1.00 TEST0001
1 Examinee096
1.00 TEST0001
1 Examinee097
1.00 TEST0001
1 Examinee098
1.00 TEST0001
1 Examinee099
1.00 TEST0001
1 Examinee100
1.00 TEST0001
1 Examinee101
1.00 TEST0001
1 Examinee102
1.00 TEST0001
1 Examinee103
1.00 TEST0001
1 Examinee104
1.00 TEST0001
1 Examinee105
1.00 TEST0001
1 Examinee106
1.00 TEST0001
1 Examinee107
1.00 TEST0001
1 Examinee108
1.00 TEST0001
1 Examinee109
1.00 TEST0001
1 Examinee110
1.00 TEST0001
1 Examinee111
1.00 TEST0001
1 Examinee112
1.00 TEST0001
1 Examinee113
1.00 TEST0001
1 Examinee114
1.00 TEST0001
25
13
25
11
25
17
25
12
25
18
25
11
25
9
25
10
25
11
25
15
25
11
25
14
25
11
25
8
25
7
25
10
25
12
25
12
25
10
25
7
|
52.00 |
|
44.00 |
|
68.00 |
|
48.00 |
|
72.00 |
|
44.00 |
|
36.00 |
|
40.00 |
|
44.00 |
|
60.00 |
|
44.00 |
|
56.00 |
|
44.00 |
|
32.00 |
|
28.00 |
|
40.00 |
|
48.00 |
|
48.00 |
|
40.00 |
|
28.00 |
|
0.8436
|
0.1145
|
2.7522
|
0.9252
|
3.0017
|
0.6986
|
-0.5793
|
-0.4542
|
0.5901
|
1.4704
|
0.2780
|
0.5299
|
0.6278
|
-1.0229
|
-2.1494
|
0.1006
|
0.9262
|
0.5557
|
-0.1136
|
-0.8151
0.7782 |
0.7395 |
0.9966 |
0.7848 |
1.0301 |
0.7675 |
0.7426 |
0.7385 |
0.7604 |
0.8385 |
0.7448 |
0.7569 |
0.7628 |
0.7742 |
1.0589 |
0.7391 |
0.7849 |
0.7584 |
0.7357 |
0.7557 |
365
1 Examinee115
1.00 TEST0001
1 Examinee116
1.00 TEST0001
1 Examinee117
1.00 TEST0001
1 Examinee118
1.00 TEST0001
1 Examinee119
1.00 TEST0001
1 Examinee120
1.00 TEST0001
1 Examinee121
1.00 TEST0001
1 Examinee122
1.00 TEST0001
1 Examinee123
1.00 TEST0001
1 Examinee124
1.00 TEST0001
1 Examinee125
1.00 TEST0001
1 Examinee126
1.00 TEST0001
1 Examinee127
1.00 TEST0001
1 Examinee128
1.00 TEST0001
1 Examinee129
1.00 TEST0001
1 Examinee130
1.00 TEST0001
1 Examinee131
1.00 TEST0001
1 Examinee132
1.00 TEST0001
1 Examinee133
1.00 TEST0001
1 Examinee134
1.00 TEST0001
25
9
25
13
25
9
25
15
25
10
25
9
25
8
25
7
25
8
25
11
25
11
25
12
25
14
25
11
25
6
25
5
25
9
25
14
25
12
25
4
|
36.00 |
|
52.00 |
|
36.00 |
|
60.00 |
|
40.00 |
|
36.00 |
|
32.00 |
|
28.00 |
|
32.00 |
|
44.00 |
|
44.00 |
|
48.00 |
|
56.00 |
|
44.00 |
|
24.00 |
|
20.00 |
|
36.00 |
|
56.00 |
|
48.00 |
|
16.00 |
|
-0.7600
|
1.3106
|
-0.5649
|
1.6283
|
-0.4313
|
-0.7259
|
-0.9365
|
-2.1096
|
-0.1227
|
0.4514
|
0.4640
|
1.0232
|
1.7345
|
0.1957
|
-1.8561
|
-1.2777
|
-0.7190
|
0.5107
|
0.0932
|
-2.9623
0.7519 |
0.8212 |
0.7421 |
0.8564 |
0.7380 |
0.7498 |
0.7656 |
1.0416 |
0.7356 |
0.7526 |
0.7533 |
0.7933 |
0.8689 |
0.7419 |
0.9463 |
0.8080 |
0.7494 |
0.7558 |
0.7390 |
1.5767 |
366
1 Examinee135
1.00 TEST0001
1 Examinee136
1.00 TEST0001
1 Examinee137
1.00 TEST0001
1 Examinee138
1.00 TEST0001
1 Examinee139
1.00 TEST0001
1 Examinee140
1.00 TEST0001
1 Examinee141
1.00 TEST0001
1 Examinee142
1.00 TEST0001
1 Examinee143
1.00 TEST0001
1 Examinee144
1.00 TEST0001
1 Examinee145
1.00 TEST0001
1 Examinee146
1.00 TEST0001
1 Examinee147
1.00 TEST0001
1 Examinee148
1.00 TEST0001
1 Examinee149
1.00 TEST0001
1 Examinee150
1.00 TEST0001
1 Examinee151
1.00 TEST0001
1 Examinee152
1.00 TEST0001
1 Examinee153
1.00 TEST0001
1 Examinee154
1.00 TEST0001
25
9
25
10
25
10
25
14
25
7
25
8
25
17
25
8
25
7
25
10
25
12
25
8
25
10
25
8
25
7
25
12
25
12
25
11
25
16
25
16
|
36.00 |
|
40.00 |
|
40.00 |
|
56.00 |
|
28.00 |
|
32.00 |
|
68.00 |
|
32.00 |
|
28.00 |
|
40.00 |
|
48.00 |
|
32.00 |
|
40.00 |
|
32.00 |
|
28.00 |
|
48.00 |
|
48.00 |
|
44.00 |
|
64.00 |
|
64.00 |
|
-0.2965
|
0.1857
|
-0.3498
|
1.2391
|
-0.2588
|
-0.6343
|
2.4058
|
-0.8730
|
-0.3485
|
-0.3178
|
0.3847
|
-0.7908
|
-0.3475
|
-0.8766
|
-0.9333
|
1.3694
|
0.8818
|
0.1368
|
1.8154
|
2.3855
0.7358 |
0.7415 |
0.7365 |
0.8139 |
0.7355 |
0.7450 |
0.9519 |
0.7601 |
0.7364 |
0.7360 |
0.7493 |
0.7540 |
0.7364 |
0.7604 |
0.7653 |
0.8274 |
0.7812 |
0.7401 |
0.8785 |
0.9494 |
367
1 Examinee155
1.00 TEST0001
1 Examinee156
1.00 TEST0001
1 Examinee157
1.00 TEST0001
1 Examinee158
1.00 TEST0001
1 Examinee159
1.00 TEST0001
1 Examinee160
1.00 TEST0001
1 Examinee161
1.00 TEST0001
1 Examinee162
1.00 TEST0001
1 Examinee163
1.00 TEST0001
1 Examinee164
1.00 TEST0001
1 Examinee165
1.00 TEST0001
1 Examinee166
1.00 TEST0001
1 Examinee167
1.00 TEST0001
1 Examinee168
1.00 TEST0001
1 Examinee169
1.00 TEST0001
1 Examinee170
1.00 TEST0001
1 Examinee171
1.00 TEST0001
1 Examinee172
1.00 TEST0001
1 Examinee173
1.00 TEST0001
1 Examinee174
1.00 TEST0001
25
10
25
10
25
16
25
15
25
19
25
16
25
17
25
5
25
10
25
17
25
7
25
12
25
8
25
13
25
16
25
9
25
7
25
14
25
10
25
17
|
40.00 |
|
40.00 |
|
64.00 |
|
60.00 |
|
76.00 |
|
64.00 |
|
68.00 |
|
20.00 |
|
40.00 |
|
68.00 |
|
28.00 |
|
48.00 |
|
32.00 |
|
52.00 |
|
64.00 |
|
36.00 |
|
28.00 |
|
56.00 |
|
40.00 |
|
68.00 |
|
0.1461
|
-0.2509
|
1.9823
|
1.5767
|
3.7143
|
1.4299
|
2.1084
|
-2.8766
|
0.5369
|
1.7806
|
-0.7161
|
0.0354
|
-0.7354
|
0.9126
|
2.1675
|
-0.8012
|
-1.0812
|
1.4300
|
0.1346
|
1.5642
0.7404 |
0.7355 |
0.8989 |
0.8504 |
1.1367 |
0.8340 |
0.9145 |
1.5056 |
0.7573 |
0.8744 |
0.7493 |
0.7377 |
0.7504 |
0.7837 |
0.9219 |
0.7547 |
0.7807 |
0.8340 |
0.7400 |
0.8490 |
368
1 Examinee175
1.00 TEST0001
1 Examinee176
1.00 TEST0001
1 Examinee177
1.00 TEST0001
1 Examinee178
1.00 TEST0001
1 Examinee179
1.00 TEST0001
1 Examinee180
1.00 TEST0001
1 Examinee181
1.00 TEST0001
1 Examinee182
1.00 TEST0001
1 Examinee183
1.00 TEST0001
1 Examinee184
1.00 TEST0001
1 Examinee185
1.00 TEST0001
1 Examinee186
1.00 TEST0001
1 Examinee187
1.00 TEST0001
1 Examinee188
1.00 TEST0001
1 Examinee189
1.00 TEST0001
1 Examinee190
1.00 TEST0001
1 Examinee191
1.00 TEST0001
1 Examinee192
1.00 TEST0001
1 Examinee193
1.00 TEST0001
1 Examinee194
1.00 TEST0001
25
17
25
14
25
8
25
12
25
9
25
11
25
13
25
13
25
9
25
12
25
9
25
11
25
10
25
12
25
12
25
8
25
11
25
8
25
12
25
12
|
68.00 |
|
56.00 |
|
32.00 |
|
48.00 |
|
36.00 |
|
44.00 |
|
52.00 |
|
52.00 |
|
36.00 |
|
48.00 |
|
36.00 |
|
44.00 |
|
40.00 |
|
48.00 |
|
48.00 |
|
32.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
48.00 |
|
2.4931
|
1.0541
|
-0.4693
|
1.1315
|
-0.1264
|
-0.0256
|
0.2137
|
0.5827
|
-0.8552
|
0.2568
|
-1.2275
|
1.1620
|
0.4524
|
0.0030
|
0.0639
|
-1.2137
|
-0.3163
|
-1.1375
|
0.4839
|
0.5026
0.9631 |
0.7961 |
0.7389 |
0.8033 |
0.7356 |
0.7366 |
0.7425 |
0.7600 |
0.7587 |
0.7440 |
0.8002 |
0.8063 |
0.7527 |
0.7371 |
0.7383 |
0.7982 |
0.7360 |
0.7877 |
0.7543 |
0.7553 |
369
1 Examinee195
1.00 TEST0001
1 Examinee196
1.00 TEST0001
1 Examinee197
1.00 TEST0001
1 Examinee198
1.00 TEST0001
1 Examinee199
1.00 TEST0001
1 Examinee200
1.00 TEST0001
1 Examinee201
1.00 TEST0001
1 Examinee202
1.00 TEST0001
1 Examinee203
1.00 TEST0001
1 Examinee204
1.00 TEST0001
1 Examinee205
1.00 TEST0001
1 Examinee206
1.00 TEST0001
1 Examinee207
1.00 TEST0001
1 Examinee208
1.00 TEST0001
1 Examinee209
1.00 TEST0001
1 Examinee210
1.00 TEST0001
1 Examinee211
1.00 TEST0001
1 Examinee212
1.00 TEST0001
1 Examinee213
1.00 TEST0001
1 Examinee214
1.00 TEST0001
25
15
25
20
25
13
25
15
25
10
25
11
25
12
25
14
25
16
25
12
25
11
25
11
25
9
25
11
25
12
25
12
25
10
25
7
25
7
25
8
|
60.00 |
|
80.00 |
|
52.00 |
|
60.00 |
|
40.00 |
|
44.00 |
|
48.00 |
|
56.00 |
|
64.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
36.00 |
|
44.00 |
|
48.00 |
|
48.00 |
|
40.00 |
|
28.00 |
|
28.00 |
|
32.00 |
|
1.7679
|
4.0000
|
1.7165
|
0.4377
|
0.0324
|
1.0925
|
0.0218
|
0.8155
|
2.7423
|
-0.1669
|
0.5237
|
-0.2945
|
-1.0231
|
0.6543
|
0.6562
|
0.5676
|
-0.6187
|
-0.5004
|
-0.6894
|
-0.3215
0.8728 |
999.0000 |
0.8667 |
0.7519 |
0.7376 |
0.7996 |
0.7374 |
0.7760 |
0.9953 |
0.7354 |
0.7565 |
0.7358 |
0.7742 |
0.7645 |
0.7646 |
0.7591 |
0.7443 |
0.7398 |
0.7478 |
0.7361 |
370
1 Examinee215
1.00 TEST0001
1 Examinee216
1.00 TEST0001
1 Examinee217
1.00 TEST0001
1 Examinee218
1.00 TEST0001
1 Examinee219
1.00 TEST0001
1 Examinee220
1.00 TEST0001
1 Examinee221
1.00 TEST0001
1 Examinee222
1.00 TEST0001
1 Examinee223
1.00 TEST0001
1 Examinee224
1.00 TEST0001
1 Examinee225
1.00 TEST0001
1 Examinee226
1.00 TEST0001
1 Examinee227
1.00 TEST0001
1 Examinee228
1.00 TEST0001
1 Examinee229
1.00 TEST0001
1 Examinee230
1.00 TEST0001
1 Examinee231
1.00 TEST0001
1 Examinee232
1.00 TEST0001
1 Examinee233
1.00 TEST0001
1 Examinee234
1.00 TEST0001
25
15
25
12
25
17
25
15
25
17
25
8
25
22
25
14
25
12
25
16
25
16
25
19
25
20
25
11
25
9
25
13
25
10
25
8
25
9
25
16
|
60.00 |
|
48.00 |
|
68.00 |
|
60.00 |
|
68.00 |
|
32.00 |
|
88.00 |
|
56.00 |
|
48.00 |
|
64.00 |
|
64.00 |
|
76.00 |
|
80.00 |
|
44.00 |
|
36.00 |
|
52.00 |
|
40.00 |
|
32.00 |
|
36.00 |
|
64.00 |
|
1.3992
|
0.2248
|
2.0206
|
2.4960
|
3.2274
|
-0.1128
|
4.0000
|
1.9688
|
0.0696
|
2.6756
|
2.0953
|
3.2939
|
4.0000
|
0.5864
|
-0.8447
|
1.3993
|
0.1750
|
-0.8320
|
0.1183
|
1.9429
0.8306 |
0.7428 |
0.9036 |
0.9634 |
1.0618 |
0.7357 |
999.0000 |
0.8972 |
0.7384 |
0.9866 |
0.9129 |
1.0714 |
999.0000 |
0.7602 |
0.7579 |
0.8307 |
0.7412 |
0.7569 |
0.7396 |
0.8940 |
371
1 Examinee235
1.00 TEST0001
1 Examinee236
1.00 TEST0001
1 Examinee237
1.00 TEST0001
1 Examinee238
1.00 TEST0001
1 Examinee239
1.00 TEST0001
1 Examinee240
1.00 TEST0001
1 Examinee241
1.00 TEST0001
1 Examinee242
1.00 TEST0001
1 Examinee243
1.00 TEST0001
1 Examinee244
1.00 TEST0001
1 Examinee245
1.00 TEST0001
1 Examinee246
1.00 TEST0001
1 Examinee247
1.00 TEST0001
1 Examinee248
1.00 TEST0001
1 Examinee249
1.00 TEST0001
1 Examinee250
1.00 TEST0001
1 Examinee251
1.00 TEST0001
1 Examinee252
1.00 TEST0001
1 Examinee253
1.00 TEST0001
1 Examinee254
1.00 TEST0001
25
9
25
12
25
11
25
11
25
16
25
10
25
13
25
14
25
9
25
10
25
8
25
12
25
7
25
12
25
8
25
8
25
10
25
12
25
5
25
12
|
36.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
64.00 |
|
40.00 |
|
52.00 |
|
56.00 |
|
36.00 |
|
40.00 |
|
32.00 |
|
48.00 |
|
28.00 |
|
48.00 |
|
32.00 |
|
32.00 |
|
40.00 |
|
48.00 |
|
20.00 |
|
48.00 |
|
-0.4840
|
0.4503
|
-1.0013
|
1.3259
|
1.8636
|
0.5081
|
0.7205
|
1.0338
|
-0.4459
|
-0.7120
|
-0.3328
|
0.1674
|
-0.7864
|
0.1769
|
-0.7488
|
-0.1672
|
-0.5189
|
0.8382
|
-2.9969
|
0.4754
0.7394 |
0.7525 |
0.7719 |
0.8228 |
0.8844 |
0.7556 |
0.7690 |
0.7942 |
0.7383 |
0.7490 |
0.7362 |
0.7410 |
0.7537 |
0.7413 |
0.7512 |
0.7354 |
0.7404 |
0.7778 |
1.6072 |
0.7539 |
372
1 Examinee255
1.00 TEST0001
1 Examinee256
1.00 TEST0001
1 Examinee257
1.00 TEST0001
1 Examinee258
1.00 TEST0001
1 Examinee259
1.00 TEST0001
1 Examinee260
1.00 TEST0001
1 Examinee261
1.00 TEST0001
1 Examinee262
1.00 TEST0001
1 Examinee263
1.00 TEST0001
1 Examinee264
1.00 TEST0001
1 Examinee265
1.00 TEST0001
1 Examinee266
1.00 TEST0001
1 Examinee267
1.00 TEST0001
1 Examinee268
1.00 TEST0001
1 Examinee269
1.00 TEST0001
1 Examinee270
1.00 TEST0001
1 Examinee271
1.00 TEST0001
1 Examinee272
1.00 TEST0001
1 Examinee273
1.00 TEST0001
1 Examinee274
1.00 TEST0001
25
9
25
17
25
9
25
16
25
14
25
12
25
15
25
12
25
9
25
9
25
6
25
7
25
5
25
14
25
6
25
11
25
8
25
7
25
9
25
14
|
36.00 |
|
68.00 |
|
36.00 |
|
64.00 |
|
56.00 |
|
48.00 |
|
60.00 |
|
48.00 |
|
36.00 |
|
36.00 |
|
24.00 |
|
28.00 |
|
20.00 |
|
56.00 |
|
24.00 |
|
44.00 |
|
32.00 |
|
28.00 |
|
36.00 |
|
56.00 |
|
-0.7222
|
2.3499
|
-0.4170
|
2.4830
|
1.5972
|
0.4982
|
1.9216
|
0.8527
|
0.2027
|
-0.1792
|
-1.4382
|
-1.3447
|
-4.0000
|
1.9728
|
-0.7025
|
0.0851
|
-0.8494
|
-0.9834
|
0.0505
|
0.7923
0.7496 |
0.9449 |
0.7377 |
0.9618 |
0.8528 |
0.7551 |
0.8914 |
0.7789 |
0.7421 |
0.7354 |
0.8369 |
0.8193 |
999.0000 |
0.8977 |
0.7485 |
0.7388 |
0.7582 |
0.7701 |
0.7380 |
0.7742 |
373
1 Examinee275
1.00 TEST0001
1 Examinee276
1.00 TEST0001
1 Examinee277
1.00 TEST0001
1 Examinee278
1.00 TEST0001
1 Examinee279
1.00 TEST0001
1 Examinee280
1.00 TEST0001
1 Examinee281
1.00 TEST0001
1 Examinee282
1.00 TEST0001
1 Examinee283
1.00 TEST0001
1 Examinee284
1.00 TEST0001
1 Examinee285
1.00 TEST0001
1 Examinee286
1.00 TEST0001
1 Examinee287
1.00 TEST0001
1 Examinee288
1.00 TEST0001
1 Examinee289
1.00 TEST0001
1 Examinee290
1.00 TEST0001
1 Examinee291
1.00 TEST0001
1 Examinee292
1.00 TEST0001
1 Examinee293
1.00 TEST0001
1 Examinee294
1.00 TEST0001
25
13
25
13
25
12
25
10
25
11
25
13
25
9
25
13
25
13
25
10
25
10
25
9
25
14
25
11
25
10
25
12
25
8
25
12
25
9
25
10
|
52.00 |
|
52.00 |
|
48.00 |
|
40.00 |
|
44.00 |
|
52.00 |
|
36.00 |
|
52.00 |
|
52.00 |
|
40.00 |
|
40.00 |
|
36.00 |
|
56.00 |
|
44.00 |
|
40.00 |
|
48.00 |
|
32.00 |
|
48.00 |
|
36.00 |
|
40.00 |
|
0.3124
|
0.7381
|
0.6447
|
-0.6476
|
-0.9532
|
1.3159
|
0.3447
|
0.7037
|
0.6848
|
0.2906
|
-0.2627
|
-0.3578
|
1.4357
|
0.3489
|
0.3399
|
0.1836
|
-1.6239
|
0.5392
|
-1.1456
|
0.2684
0.7462 |
0.7703 |
0.7639 |
0.7456 |
0.7671 |
0.8218 |
0.7475 |
0.7678 |
0.7665 |
0.7453 |
0.7356 |
0.7366 |
0.8346 |
0.7477 |
0.7473 |
0.7415 |
0.8789 |
0.7574 |
0.7888 |
0.7444 |
374
1 Examinee295
1.00 TEST0001
1 Examinee296
1.00 TEST0001
1 Examinee297
1.00 TEST0001
1 Examinee298
1.00 TEST0001
1 Examinee299
1.00 TEST0001
1 Examinee300
1.00 TEST0001
1 Examinee301
1.00 TEST0001
1 Examinee302
1.00 TEST0001
1 Examinee303
1.00 TEST0001
1 Examinee304
1.00 TEST0001
1 Examinee305
1.00 TEST0001
1 Examinee306
1.00 TEST0001
1 Examinee307
1.00 TEST0001
1 Examinee308
1.00 TEST0001
1 Examinee309
1.00 TEST0001
1 Examinee310
1.00 TEST0001
1 Examinee311
1.00 TEST0001
1 Examinee312
1.00 TEST0001
1 Examinee313
1.00 TEST0001
1 Examinee314
1.00 TEST0001
25
13
25
13
25
10
25
13
25
10
25
9
25
13
25
10
25
5
25
10
25
14
25
6
25
13
25
12
25
14
25
14
25
9
25
9
25
5
25
7
|
52.00 |
|
52.00 |
|
40.00 |
|
52.00 |
|
40.00 |
|
36.00 |
|
52.00 |
|
40.00 |
|
20.00 |
|
40.00 |
|
56.00 |
|
24.00 |
|
52.00 |
|
48.00 |
|
56.00 |
|
56.00 |
|
36.00 |
|
36.00 |
|
20.00 |
|
28.00 |
|
-0.0862
|
0.1485
|
-0.0794
|
0.1166
|
0.1808
|
-0.6047
|
0.3334
|
0.0425
|
-1.4780
|
-0.5990
|
1.4871
|
-1.2399
|
0.5024
|
0.1573
|
0.3507
|
1.2250
|
-0.7819
|
-0.6147
|
-1.9815
|
-0.8217
0.7359 |
0.7404 |
0.7360 |
0.7395 |
0.7414 |
0.7437 |
0.7470 |
0.7378 |
0.8451 |
0.7434 |
0.8403 |
0.8021 |
0.7553 |
0.7407 |
0.7478 |
0.8125 |
0.7534 |
0.7441 |
0.9904 |
0.7561 |
375
1 Examinee315
1.00 TEST0001
1 Examinee316
1.00 TEST0001
1 Examinee317
1.00 TEST0001
1 Examinee318
1.00 TEST0001
1 Examinee319
1.00 TEST0001
1 Examinee320
1.00 TEST0001
1 Examinee321
1.00 TEST0001
1 Examinee322
1.00 TEST0001
1 Examinee323
1.00 TEST0001
1 Examinee324
1.00 TEST0001
1 Examinee325
1.00 TEST0001
1 Examinee326
1.00 TEST0001
1 Examinee327
1.00 TEST0001
1 Examinee328
1.00 TEST0001
1 Examinee329
1.00 TEST0001
1 Examinee330
1.00 TEST0001
1 Examinee331
1.00 TEST0001
1 Examinee332
1.00 TEST0001
1 Examinee333
1.00 TEST0001
1 Examinee334
1.00 TEST0001
25
4
25
7
25
15
25
11
25
8
25
8
25
8
25
19
25
15
25
12
25
12
25
11
25
8
25
12
25
12
25
14
25
14
25
13
25
8
25
14
|
16.00 |
|
28.00 |
|
60.00 |
|
44.00 |
|
32.00 |
|
32.00 |
|
32.00 |
|
76.00 |
|
60.00 |
|
48.00 |
|
48.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
48.00 |
|
56.00 |
|
56.00 |
|
52.00 |
|
32.00 |
|
56.00 |
|
-1.8643
|
-1.0981
|
1.6737
|
1.0778
|
0.0596
|
-1.2400
|
-0.5678
|
3.9714
|
1.3523
|
0.9189
|
0.1558
|
-0.4765
|
-0.7360
|
-0.2879
|
0.7576
|
1.5338
|
0.7492
|
0.5439
|
-0.7353
|
1.7395
0.9491 |
0.7828 |
0.8617 |
0.7983 |
0.7382 |
0.8021 |
0.7422 |
1.1804 |
0.8256 |
0.7843 |
0.7406 |
0.7391 |
0.7504 |
0.7357 |
0.7717 |
0.8456 |
0.7711 |
0.7577 |
0.7504 |
0.8695 |
376
1 Examinee335
1.00 TEST0001
1 Examinee336
1.00 TEST0001
1 Examinee337
1.00 TEST0001
1 Examinee338
1.00 TEST0001
1 Examinee339
1.00 TEST0001
1 Examinee340
1.00 TEST0001
1 Examinee341
1.00 TEST0001
1 Examinee342
1.00 TEST0001
1 Examinee343
1.00 TEST0001
1 Examinee344
1.00 TEST0001
1 Examinee345
1.00 TEST0001
1 Examinee346
1.00 TEST0001
1 Examinee347
1.00 TEST0001
1 Examinee348
1.00 TEST0001
1 Examinee349
1.00 TEST0001
1 Examinee350
1.00 TEST0001
1 Examinee351
1.00 TEST0001
1 Examinee352
1.00 TEST0001
1 Examinee353
1.00 TEST0001
1 Examinee354
1.00 TEST0001
25
9
25
12
25
13
25
14
25
13
25
12
25
13
25
11
25
8
25
6
25
12
25
7
25
11
25
14
25
11
25
6
25
9
25
14
25
10
25
10
|
36.00 |
|
48.00 |
|
52.00 |
|
56.00 |
|
52.00 |
|
48.00 |
|
52.00 |
|
44.00 |
|
32.00 |
|
24.00 |
|
48.00 |
|
28.00 |
|
44.00 |
|
56.00 |
|
44.00 |
|
24.00 |
|
36.00 |
|
56.00 |
|
40.00 |
|
40.00 |
|
-0.3485
|
0.5114
|
0.8208
|
0.9036
|
0.9366
|
-0.6630
|
1.5691
|
0.6771
|
-0.9701
|
-2.8755
|
0.5826
|
-1.5366
|
0.6665
|
1.3041
|
0.3087
|
-0.6055
|
-0.8529
|
1.9414
|
-1.0711
|
-0.3234
0.7364 |
0.7558 |
0.7764 |
0.7830 |
0.7858 |
0.7464 |
0.8496 |
0.7660 |
0.7688 |
1.5046 |
0.7600 |
0.8580 |
0.7653 |
0.8206 |
0.7460 |
0.7437 |
0.7585 |
0.8939 |
0.7796 |
0.7361 |
377
1 Examinee355
1.00 TEST0001
1 Examinee356
1.00 TEST0001
1 Examinee357
1.00 TEST0001
1 Examinee358
1.00 TEST0001
1 Examinee359
1.00 TEST0001
1 Examinee360
1.00 TEST0001
1 Examinee361
1.00 TEST0001
1 Examinee362
1.00 TEST0001
1 Examinee363
1.00 TEST0001
1 Examinee364
1.00 TEST0001
1 Examinee365
1.00 TEST0001
1 Examinee366
1.00 TEST0001
1 Examinee367
1.00 TEST0001
1 Examinee368
1.00 TEST0001
1 Examinee369
1.00 TEST0001
1 Examinee370
1.00 TEST0001
1 Examinee371
1.00 TEST0001
1 Examinee372
1.00 TEST0001
1 Examinee373
1.00 TEST0001
1 Examinee374
1.00 TEST0001
25
12
25
11
25
8
25
13
25
15
25
11
25
12
25
10
25
9
25
13
25
9
25
6
25
13
25
12
25
13
25
8
25
10
25
11
25
8
25
9
|
48.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
60.00 |
|
44.00 |
|
48.00 |
|
40.00 |
|
36.00 |
|
52.00 |
|
36.00 |
|
24.00 |
|
52.00 |
|
48.00 |
|
52.00 |
|
32.00 |
|
40.00 |
|
44.00 |
|
32.00 |
|
36.00 |
|
-0.2761
|
-0.8021
|
-0.3720
|
1.2318
|
1.5379
|
0.0470
|
0.6215
|
-0.7460
|
0.1371
|
0.2040
|
-0.7759
|
-1.9509
|
0.9447
|
1.0608
|
0.3518
|
-0.2346
|
-0.5628
|
-0.7695
|
-0.8341
|
-0.7411
0.7356 |
0.7547 |
0.7368 |
0.8131 |
0.8460 |
0.7379 |
0.7624 |
0.7510 |
0.7401 |
0.7421 |
0.7530 |
0.9791 |
0.7864 |
0.7967 |
0.7478 |
0.7354 |
0.7420 |
0.7525 |
0.7571 |
0.7507 |
378
1 Examinee375
1.00 TEST0001
1 Examinee376
1.00 TEST0001
1 Examinee377
1.00 TEST0001
1 Examinee378
1.00 TEST0001
1 Examinee379
1.00 TEST0001
1 Examinee380
1.00 TEST0001
1 Examinee381
1.00 TEST0001
1 Examinee382
1.00 TEST0001
1 Examinee383
1.00 TEST0001
1 Examinee384
1.00 TEST0001
1 Examinee385
1.00 TEST0001
1 Examinee386
1.00 TEST0001
1 Examinee387
1.00 TEST0001
1 Examinee388
1.00 TEST0001
1 Examinee389
1.00 TEST0001
1 Examinee390
1.00 TEST0001
1 Examinee391
1.00 TEST0001
1 Examinee392
1.00 TEST0001
1 Examinee393
1.00 TEST0001
1 Examinee394
1.00 TEST0001
25
10
25
11
25
12
25
3
25
7
25
8
25
13
25
7
25
11
25
13
25
15
25
10
25
9
25
11
25
8
25
6
25
11
25
12
25
12
25
10
|
40.00 |
|
44.00 |
|
48.00 |
|
12.00 |
|
28.00 |
|
32.00 |
|
52.00 |
|
28.00 |
|
44.00 |
|
52.00 |
|
60.00 |
|
40.00 |
|
36.00 |
|
44.00 |
|
32.00 |
|
24.00 |
|
44.00 |
|
48.00 |
|
48.00 |
|
40.00 |
|
-1.1689
|
0.2258
|
0.4518
|
-2.2968
|
-1.4387
|
-0.2622
|
0.6567
|
-1.4310
|
-0.0318
|
0.3615
|
1.5899
|
-1.2145
|
0.0880
|
-0.0259
|
-0.8657
|
-0.6113
|
0.3610
|
0.6283
|
0.4251
|
0.0168
0.7919 |
0.7429 |
0.7526 |
1.1287 |
0.8370 |
0.7356 |
0.7647 |
0.8355 |
0.7365 |
0.7483 |
0.8519 |
0.7983 |
0.7388 |
0.7366 |
0.7595 |
0.7440 |
0.7482 |
0.7628 |
0.7513 |
0.7373 |
379
1 Examinee395
1.00 TEST0001
1 Examinee396
1.00 TEST0001
1 Examinee397
1.00 TEST0001
1 Examinee398
1.00 TEST0001
1 Examinee399
1.00 TEST0001
1 Examinee400
1.00 TEST0001
1 Examinee401
1.00 TEST0001
1 Examinee402
1.00 TEST0001
1 Examinee403
1.00 TEST0001
1 Examinee404
1.00 TEST0001
1 Examinee405
1.00 TEST0001
1 Examinee406
1.00 TEST0001
1 Examinee407
1.00 TEST0001
1 Examinee408
1.00 TEST0001
1 Examinee409
1.00 TEST0001
1 Examinee410
1.00 TEST0001
1 Examinee411
1.00 TEST0001
1 Examinee412
1.00 TEST0001
1 Examinee413
1.00 TEST0001
1 Examinee414
1.00 TEST0001
25
10
25
7
25
7
25
9
25
12
25
11
25
11
25
11
25
12
25
17
25
11
25
10
25
11
25
6
25
12
25
12
25
9
25
6
25
9
25
12
|
40.00 |
|
28.00 |
|
28.00 |
|
36.00 |
|
48.00 |
|
44.00 |
|
44.00 |
|
44.00 |
|
48.00 |
|
68.00 |
|
44.00 |
|
40.00 |
|
44.00 |
|
24.00 |
|
48.00 |
|
48.00 |
|
36.00 |
|
24.00 |
|
36.00 |
|
48.00 |
|
0.5886
|
-1.1819
|
-0.9518
|
-1.1873
|
0.2010
|
-0.3572
|
0.0798
|
0.5000
|
1.3204
|
2.1653
|
0.3541
|
-0.6347
|
-0.4154
|
-2.0249
|
-0.0921
|
-0.7554
|
-1.6881
|
-1.7891
|
-0.0104
|
0.3313
0.7603 |
0.7937 |
0.7670 |
0.7944 |
0.7420 |
0.7366 |
0.7386 |
0.7552 |
0.8223 |
0.9216 |
0.7479 |
0.7450 |
0.7376 |
1.0070 |
0.7358 |
0.7516 |
0.8958 |
0.9250 |
0.7369 |
0.7469 |
380
1 Examinee415
1.00 TEST0001
1 Examinee416
1.00 TEST0001
1 Examinee417
1.00 TEST0001
1 Examinee418
1.00 TEST0001
1 Examinee419
1.00 TEST0001
1 Examinee420
1.00 TEST0001
1 Examinee421
1.00 TEST0001
1 Examinee422
1.00 TEST0001
1 Examinee423
1.00 TEST0001
1 Examinee424
1.00 TEST0001
1 Examinee425
1.00 TEST0001
1 Examinee426
1.00 TEST0001
1 Examinee427
1.00 TEST0001
1 Examinee428
1.00 TEST0001
1 Examinee429
1.00 TEST0001
1 Examinee430
1.00 TEST0001
1 Examinee431
1.00 TEST0001
1 Examinee432
1.00 TEST0001
1 Examinee433
1.00 TEST0001
1 Examinee434
1.00 TEST0001
25
13
25
12
25
7
25
16
25
9
25
13
25
6
25
14
25
7
25
8
25
13
25
13
25
7
25
10
25
8
25
10
25
13
25
12
25
8
25
14
|
52.00 |
|
48.00 |
|
28.00 |
|
64.00 |
|
36.00 |
|
52.00 |
|
24.00 |
|
56.00 |
|
28.00 |
|
32.00 |
|
52.00 |
|
52.00 |
|
28.00 |
|
40.00 |
|
32.00 |
|
40.00 |
|
52.00 |
|
48.00 |
|
32.00 |
|
56.00 |
|
1.0315
|
-0.5490
|
-1.0974
|
2.1284
|
-0.0779
|
0.4648
|
-1.2682
|
1.0609
|
-2.0850
|
-0.6443
|
0.1737
|
1.1337
|
-2.7697
|
0.2101
|
-0.1369
|
-0.4816
|
-0.3379
|
-0.0431
|
-0.7141
|
1.2673
0.7940 |
0.7415 |
0.7827 |
0.9170 |
0.7360 |
0.7533 |
0.8065 |
0.7967 |
1.0313 |
0.7455 |
0.7412 |
0.8035 |
1.4224 |
0.7423 |
0.7355 |
0.7393 |
0.7363 |
0.7364 |
0.7491 |
0.8167 |
381
1 Examinee435
1.00 TEST0001
1 Examinee436
1.00 TEST0001
1 Examinee437
1.00 TEST0001
1 Examinee438
1.00 TEST0001
1 Examinee439
1.00 TEST0001
1 Examinee440
1.00 TEST0001
1 Examinee441
1.00 TEST0001
1 Examinee442
1.00 TEST0001
1 Examinee443
1.00 TEST0001
1 Examinee444
1.00 TEST0001
1 Examinee445
1.00 TEST0001
1 Examinee446
1.00 TEST0001
1 Examinee447
1.00 TEST0001
1 Examinee448
1.00 TEST0001
1 Examinee449
1.00 TEST0001
1 Examinee450
1.00 TEST0001
1 Examinee451
1.00 TEST0001
1 Examinee452
1.00 TEST0001
1 Examinee453
1.00 TEST0001
1 Examinee454
1.00 TEST0001
25
15
25
6
25
12
25
9
25
7
25
7
25
13
25
11
25
8
25
13
25
7
25
11
25
12
25
9
25
12
25
10
25
9
25
13
25
14
25
14
|
60.00 |
|
24.00 |
|
48.00 |
|
36.00 |
|
28.00 |
|
28.00 |
|
52.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
28.00 |
|
44.00 |
|
48.00 |
|
36.00 |
|
48.00 |
|
40.00 |
|
36.00 |
|
52.00 |
|
56.00 |
|
56.00 |
|
1.4892
|
-1.6325
|
-0.0614
|
0.5064
|
-1.3256
|
-1.5769
|
-0.2950
|
0.4814
|
-0.7533
|
1.0506
|
-0.1948
|
0.3729
|
0.7694
|
0.2389
|
0.6399
|
0.0634
|
-0.4922
|
-0.8171
|
1.5470
|
1.2265
0.8406 |
0.8811 |
0.7362 |
0.7555 |
0.8160 |
0.8673 |
0.7358 |
0.7542 |
0.7515 |
0.7958 |
0.7354 |
0.7488 |
0.7725 |
0.7433 |
0.7636 |
0.7383 |
0.7396 |
0.7558 |
0.8471 |
0.8126 |
382
1 Examinee455
1.00 TEST0001
1 Examinee456
1.00 TEST0001
1 Examinee457
1.00 TEST0001
1 Examinee458
1.00 TEST0001
1 Examinee459
1.00 TEST0001
1 Examinee460
1.00 TEST0001
1 Examinee461
1.00 TEST0001
1 Examinee462
1.00 TEST0001
1 Examinee463
1.00 TEST0001
1 Examinee464
1.00 TEST0001
1 Examinee465
1.00 TEST0001
1 Examinee466
1.00 TEST0001
1 Examinee467
1.00 TEST0001
1 Examinee468
1.00 TEST0001
1 Examinee469
1.00 TEST0001
1 Examinee470
1.00 TEST0001
1 Examinee471
1.00 TEST0001
1 Examinee472
1.00 TEST0001
1 Examinee473
1.00 TEST0001
1 Examinee474
1.00 TEST0001
25
9
25
11
25
11
25
10
25
13
25
16
25
11
25
8
25
12
25
9
25
7
25
7
25
11
25
18
25
10
25
8
25
12
25
10
25
10
25
10
|
36.00 |
|
44.00 |
|
44.00 |
|
40.00 |
|
52.00 |
|
64.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
36.00 |
|
28.00 |
|
28.00 |
|
44.00 |
|
72.00 |
|
40.00 |
|
32.00 |
|
48.00 |
|
40.00 |
|
40.00 |
|
40.00 |
|
-0.3140
|
-0.7280
|
-0.3188
|
0.7441
|
0.6346
|
2.6927
|
-0.6003
|
-0.9574
|
0.0882
|
-0.3052
|
-0.5703
|
-1.3286
|
-0.2564
|
3.1645
|
0.1734
|
-0.8100
|
0.5121
|
0.2980
|
-0.0031
|
0.0868
0.7360 |
0.7500 |
0.7361 |
0.7707 |
0.7632 |
0.9888 |
0.7435 |
0.7675 |
0.7388 |
0.7359 |
0.7423 |
0.8165 |
0.7355 |
1.0527 |
0.7412 |
0.7553 |
0.7559 |
0.7456 |
0.7370 |
0.7388 |
383
1 Examinee475
1.00 TEST0001
1 Examinee476
1.00 TEST0001
1 Examinee477
1.00 TEST0001
1 Examinee478
1.00 TEST0001
1 Examinee479
1.00 TEST0001
1 Examinee480
1.00 TEST0001
1 Examinee481
1.00 TEST0001
1 Examinee482
1.00 TEST0001
1 Examinee483
1.00 TEST0001
1 Examinee484
1.00 TEST0001
1 Examinee485
1.00 TEST0001
1 Examinee486
1.00 TEST0001
1 Examinee487
1.00 TEST0001
1 Examinee488
1.00 TEST0001
1 Examinee489
1.00 TEST0001
1 Examinee490
1.00 TEST0001
1 Examinee491
1.00 TEST0001
1 Examinee492
1.00 TEST0001
1 Examinee493
1.00 TEST0001
1 Examinee494
1.00 TEST0001
25
9
25
11
25
8
25
12
25
8
25
9
25
10
25
11
25
10
25
12
25
16
25
10
25
11
25
9
25
14
25
13
25
14
25
14
25
17
25
13
|
36.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
32.00 |
|
36.00 |
|
40.00 |
|
44.00 |
|
40.00 |
|
48.00 |
|
64.00 |
|
40.00 |
|
44.00 |
|
36.00 |
|
56.00 |
|
52.00 |
|
56.00 |
|
56.00 |
|
68.00 |
|
52.00 |
|
-0.7600
|
0.1140
|
-0.2667
|
0.2571
|
-0.4707
|
0.0817
|
0.2741
|
-0.6283
|
0.2674
|
0.0512
|
2.0163
|
-0.0299
|
0.2300
|
0.1559
|
0.5696
|
1.4964
|
1.2382
|
0.6263
|
1.8714
|
0.0113
0.7519 |
0.7395 |
0.7356 |
0.7440 |
0.7390 |
0.7387 |
0.7446 |
0.7447 |
0.7444 |
0.7380 |
0.9031 |
0.7366 |
0.7430 |
0.7406 |
0.7592 |
0.8414 |
0.8138 |
0.7627 |
0.8853 |
0.7372 |
384
1 Examinee495
1.00 TEST0001
1 Examinee496
1.00 TEST0001
1 Examinee497
1.00 TEST0001
1 Examinee498
1.00 TEST0001
1 Examinee499
1.00 TEST0001
1 Examinee500
1.00 TEST0001
1 Examinee501
1.00 TEST0001
1 Examinee502
1.00 TEST0001
1 Examinee503
1.00 TEST0001
1 Examinee504
1.00 TEST0001
1 Examinee505
1.00 TEST0001
1 Examinee506
1.00 TEST0001
1 Examinee507
1.00 TEST0001
1 Examinee508
1.00 TEST0001
1 Examinee509
1.00 TEST0001
1 Examinee510
1.00 TEST0001
1 Examinee511
1.00 TEST0001
1 Examinee512
1.00 TEST0001
1 Examinee513
1.00 TEST0001
1 Examinee514
1.00 TEST0001
25
6
25
16
25
12
25
7
25
13
25
10
25
12
25
10
25
6
25
9
25
19
25
14
25
15
25
15
25
12
25
13
25
12
25
12
25
12
25
12
|
24.00 |
|
64.00 |
|
48.00 |
|
28.00 |
|
52.00 |
|
40.00 |
|
48.00 |
|
40.00 |
|
24.00 |
|
36.00 |
|
76.00 |
|
56.00 |
|
60.00 |
|
60.00 |
|
48.00 |
|
52.00 |
|
48.00 |
|
48.00 |
|
48.00 |
|
48.00 |
|
-1.1911
|
0.9964
|
0.5627
|
-1.9313
|
0.7143
|
-0.4937
|
-0.0866
|
0.2228
|
-1.0593
|
0.1551
|
3.4405
|
1.4070
|
1.4852
|
1.1945
|
0.3828
|
0.5484
|
0.1448
|
1.0626
|
-0.0145
|
0.8964
0.7950 |
0.7909 |
0.7588 |
0.9721 |
0.7686 |
0.7396 |
0.7359 |
0.7428 |
0.7782 |
0.7406 |
1.0934 |
0.8315 |
0.8401 |
0.8094 |
0.7492 |
0.7579 |
0.7403 |
0.7969 |
0.7368 |
0.7824 |
385
1 Examinee515
1.00 TEST0001
1 Examinee516
1.00 TEST0001
1 Examinee517
1.00 TEST0001
1 Examinee518
1.00 TEST0001
1 Examinee519
1.00 TEST0001
1 Examinee520
1.00 TEST0001
1 Examinee521
1.00 TEST0001
1 Examinee522
1.00 TEST0001
1 Examinee523
1.00 TEST0001
1 Examinee524
1.00 TEST0001
1 Examinee525
1.00 TEST0001
1 Examinee526
1.00 TEST0001
1 Examinee527
1.00 TEST0001
1 Examinee528
1.00 TEST0001
1 Examinee529
1.00 TEST0001
1 Examinee530
1.00 TEST0001
1 Examinee531
1.00 TEST0001
1 Examinee532
1.00 TEST0001
1 Examinee533
1.00 TEST0001
1 Examinee534
1.00 TEST0001
25
12
25
6
25
14
25
13
25
10
25
10
25
11
25
8
25
13
25
13
25
17
25
9
25
8
25
10
25
8
25
9
25
5
25
11
25
11
25
9
|
48.00 |
|
24.00 |
|
56.00 |
|
52.00 |
|
40.00 |
|
40.00 |
|
44.00 |
|
32.00 |
|
52.00 |
|
52.00 |
|
68.00 |
|
36.00 |
|
32.00 |
|
40.00 |
|
32.00 |
|
36.00 |
|
20.00 |
|
44.00 |
|
44.00 |
|
36.00 |
|
0.7334
|
-0.8534
|
1.4455
|
-0.0223
|
0.7223
|
-0.2289
|
0.2943
|
-0.7301
|
0.4741
|
1.0281
|
2.6467
|
-0.6984
|
-0.3939
|
-0.4427
|
-0.6490
|
-0.3943
|
-2.9951
|
0.0043
|
0.9790
|
-0.5080
0.7699 |
0.7585 |
0.8357 |
0.7367 |
0.7691 |
0.7354 |
0.7454 |
0.7501 |
0.7538 |
0.7937 |
0.9828 |
0.7483 |
0.7372 |
0.7383 |
0.7457 |
0.7372 |
1.6051 |
0.7371 |
0.7894 |
0.7401 |
386
1 Examinee535
1.00 TEST0001
1 Examinee536
1.00 TEST0001
1 Examinee537
1.00 TEST0001
1 Examinee538
1.00 TEST0001
1 Examinee539
1.00 TEST0001
1 Examinee540
1.00 TEST0001
1 Examinee541
1.00 TEST0001
1 Examinee542
1.00 TEST0001
1 Examinee543
1.00 TEST0001
1 Examinee544
1.00 TEST0001
1 Examinee545
1.00 TEST0001
1 Examinee546
1.00 TEST0001
1 Examinee547
1.00 TEST0001
1 Examinee548
1.00 TEST0001
1 Examinee549
1.00 TEST0001
1 Examinee550
1.00 TEST0001
1 Examinee551
1.00 TEST0001
1 Examinee552
1.00 TEST0001
1 Examinee553
1.00 TEST0001
1 Examinee554
1.00 TEST0001
25
12
25
9
25
12
25
8
25
13
25
7
25
15
25
16
25
9
25
10
25
10
25
13
25
7
25
5
25
10
25
4
25
4
25
6
25
6
25
5
|
48.00 |
|
36.00 |
|
48.00 |
|
32.00 |
|
52.00 |
|
28.00 |
|
60.00 |
|
64.00 |
|
36.00 |
|
40.00 |
|
40.00 |
|
52.00 |
|
28.00 |
|
20.00 |
|
40.00 |
|
16.00 |
|
16.00 |
|
24.00 |
|
24.00 |
|
20.00 |
|
0.6138 0.7619 |
|
-0.3725 0.7368 |
|
1.4902 0.8407 |
|
-0.9142 0.7636 |
|
0.9875 0.7901 |
|
-1.4576 0.8409 |
|
2.6498 0.9832 |
|
2.4701 0.9601 |
|
-0.6858 0.7476 |
|
-0.6405 0.7453 |
|
0.1277 0.7398 |
|
1.0608 0.7967 |
|
-2.7009 1.3725 |
|
-3.2572 1.8567 |
|
-0.1610 0.7354 |
|
-3.2190 1.8173 |
|
-4.0000 999.0000 |
|
-2.6912 1.3657 |
|
-2.5816 1.2919 |
|
-3.2865 1.8878 |
387
1 Examinee555
1.00 TEST0001
1 Examinee556
1.00 TEST0001
1 Examinee557
1.00 TEST0001
1 Examinee558
1.00 TEST0001
1 Examinee559
1.00 TEST0001
1 Examinee560
1.00 TEST0001
1 Examinee561
1.00 TEST0001
1 Examinee562
1.00 TEST0001
1 Examinee563
1.00 TEST0001
1 Examinee564
1.00 TEST0001
1 Examinee565
1.00 TEST0001
1 Examinee566
1.00 TEST0001
1 Examinee567
1.00 TEST0001
1 Examinee568
1.00 TEST0001
1 Examinee569
1.00 TEST0001
1 Examinee570
1.00 TEST0001
1 Examinee571
1.00 TEST0001
1 Examinee572
1.00 TEST0001
1 Examinee573
1.00 TEST0001
1 Examinee574
1.00 TEST0001
25
7
25
7
25
2
25
3
25
6
25
2
25
5
25
8
25
7
25
8
25
9
25
8
25
9
25
3
25
4
25
7
25
5
25
3
25
6
25
4
|
28.00 |
|
28.00 |
|
8.00 |
|
12.00 |
|
24.00 |
|
8.00 |
|
20.00 |
|
32.00 |
|
28.00 |
|
32.00 |
|
36.00 |
|
32.00 |
|
36.00 |
|
12.00 |
|
16.00 |
|
28.00 |
|
20.00 |
|
12.00 |
|
24.00 |
|
16.00 |
|
-3.7333 2.4435 |
|
-1.8887 0.9572 |
|
-4.0000 999.0000 |
|
-4.0000 999.0000 |
|
-3.4974 2.1279 |
|
-4.0000 999.0000 |
|
-4.0000 999.0000 |
|
-1.8450 0.9427 |
|
-1.2477 0.8033 |
|
-2.2845 1.1225 |
|
-0.9680 0.7686 |
|
-2.0146 1.0031 |
|
-2.6094 1.3103 |
|
-4.0000 999.0000 |
|
-2.7631 1.4177 |
|
-2.9890 1.5998 |
|
-4.0000 999.0000 |
|
-4.0000 999.0000 |
|
-4.0000 999.0000 |
|
-4.0000 999.0000 |
388
1 Examinee575
1.00 TEST0001
1 Examinee576
1.00 TEST0001
1 Examinee577
1.00 TEST0001
1 Examinee578
1.00 TEST0001
1 Examinee579
1.00 TEST0001
1 Examinee580
1.00 TEST0001
1 Examinee581
1.00 TEST0001
1 Examinee582
1.00 TEST0001
1 Examinee583
1.00 TEST0001
1 Examinee584
1.00 TEST0001
1 Examinee585
1.00 TEST0001
1 Examinee586
1.00 TEST0001
1 Examinee587
1.00 TEST0001
1 Examinee588
1.00 TEST0001
1 Examinee589
1.00 TEST0001
1 Examinee590
1.00 TEST0001
1 Examinee591
1.00 TEST0001
1 Examinee592
1.00 TEST0001
1 Examinee593
1.00 TEST0001
1 Examinee594
1.00 TEST0001
25
8
25
2
25
3
25
10
25
1
25
10
25
8
25
12
25
8
25
10
25
14
25
9
25
12
25
12
25
14
25
8
25
13
25
7
25
15
25
12
|
|
32.00 | -1.7802 0.9223 |
|
|
8.00 | -4.0000 999.0000 |
|
|
12.00 | -4.0000 999.0000 |
|
|
40.00 | -1.3214 0.8153 |
|
|
4.00 | -4.0000 999.0000 |
|
|
40.00 | 0.4671 0.7534 |
|
|
32.00 | 0.0504 0.7380 |
|
|
48.00 | 0.3888 0.7495 |
|
|
32.00 | -0.7513 0.7514 |
|
|
40.00 | 0.2426 0.7435 |
|
|
56.00 | 0.6005 0.7611 |
|
|
36.00 | -0.7449 0.7510 |
|
|
48.00 | 0.7462 0.7708 |
|
|
48.00 | 0.3988 0.7500 |
|
|
56.00 | 1.5866 0.8516 |
|
|
32.00 | -0.9158 0.7637 |
|
|
52.00 | 0.5054 0.7555 |
|
|
28.00 | -0.9182 0.7639 |
|
|
60.00 | 0.8342 0.7774 |
|
|
48.00 | -0.2237 0.7354 |
389
1 Examinee595
1.00 TEST0001
1 Examinee596
1.00 TEST0001
1 Examinee597
1.00 TEST0001
1 Examinee598
1.00 TEST0001
1 Examinee599
1.00 TEST0001
1 Examinee600
1.00 TEST0001
1 Examinee601
1.00 TEST0001
1 Examinee602
1.00 TEST0001
1 Examinee603
1.00 TEST0001
1 Examinee604
1.00 TEST0001
1 Examinee605
1.00 TEST0001
1 Examinee606
1.00 TEST0001
1 Examinee607
1.00 TEST0001
1 Examinee608
1.00 TEST0001
1 Examinee609
1.00 TEST0001
1 Examinee610
1.00 TEST0001
1 Examinee611
1.00 TEST0001
1 Examinee612
1.00 TEST0001
1 Examinee613
1.00 TEST0001
1 Examinee614
1.00 TEST0001
25
12
25
8
25
14
25
7
25
8
25
11
25
9
25
12
25
9
25
12
25
8
25
7
25
10
25
6
25
13
25
9
25
13
25
2
25
13
25
11
|
|
48.00 | -0.1319 0.7355 |
|
|
32.00 | -1.3625 0.8225 |
|
|
56.00 | 1.2692 0.8170 |
|
|
28.00 | -1.4555 0.8404 |
|
|
32.00 | -0.7182 0.7494 |
|
|
44.00 | 0.7238 0.7693 |
|
|
36.00 | -1.1790 0.7933 |
|
|
48.00 | -0.3798 0.7369 |
|
|
36.00 | -1.1918 0.7951 |
|
|
48.00 | 0.3870 0.7494 |
|
|
32.00 | -1.8786 0.9537 |
|
|
28.00 | -1.2697 0.8067 |
|
|
40.00 | -0.1283 0.7356 |
|
|
24.00 | -1.1141 0.7847 |
|
|
52.00 | 1.1347 0.8036 |
|
|
36.00 | -0.2496 0.7355 |
|
|
52.00 | -0.4470 0.7384 |
|
|
8.00 | -4.0000 999.0000 |
|
|
52.00 | 1.1948 0.8095 |
|
|
44.00 | 0.1720 0.7411 |
390
1 Examinee615
1.00 TEST0001
1 Examinee616
1.00 TEST0001
1 Examinee617
1.00 TEST0001
1 Examinee618
1.00 TEST0001
1 Examinee619
1.00 TEST0001
1 Examinee620
1.00 TEST0001
1 Examinee621
1.00 TEST0001
1 Examinee622
1.00 TEST0001
1 Examinee623
1.00 TEST0001
1 Examinee624
1.00 TEST0001
1 Examinee625
1.00 TEST0001
1 Examinee626
1.00 TEST0001
1 Examinee627
1.00 TEST0001
1 Examinee628
1.00 TEST0001
1 Examinee629
1.00 TEST0001
1 Examinee630
1.00 TEST0001
1 Examinee631
1.00 TEST0001
1 Examinee632
1.00 TEST0001
1 Examinee633
1.00 TEST0001
1 Examinee634
1.00 TEST0001
25
12
25
8
25
13
25
15
25
10
25
8
25
8
25
10
25
9
25
14
25
11
25
11
25
16
25
10
25
6
25
9
25
14
25
11
25
15
25
8
|
48.00 |
|
32.00 |
|
52.00 |
|
60.00 |
|
40.00 |
|
32.00 |
|
32.00 |
|
40.00 |
|
36.00 |
|
56.00 |
|
44.00 |
|
44.00 |
|
64.00 |
|
40.00 |
|
24.00 |
|
36.00 |
|
56.00 |
|
44.00 |
|
60.00 |
|
32.00 |
|
0.7236
|
-1.2977
|
0.3967
|
1.9204
|
0.0921
|
-1.1857
|
-0.9052
|
0.5566
|
-1.3831
|
1.6851
|
0.5698
|
0.2103
|
1.8821
|
0.0338
|
-1.1782
|
-0.3562
|
1.4298
|
-0.1813
|
2.0658
|
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0.7499 |
0.8913 |
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0.7942 |
0.7628 |
0.7584 |
0.8263 |
0.8630 |
0.7592 |
0.7423 |
0.8866 |
0.7376 |
0.7932 |
0.7366 |
0.8340 |
0.7354 |
0.9092 |
0.8544 |
391
1 Examinee635
1.00 TEST0001
1 Examinee636
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1 Examinee637
1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
25
12
25
12
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13
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18
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9
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17
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19
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48.00 |
|
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72.00 |
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44.00 |
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36.00 |
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32.00 |
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28.00 |
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0.7572 |
0.8563 |
0.7824 |
0.7496 |
0.7771 |
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0.8421 |
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1.0507 |
999.0000 |
392
1 Examinee655
1.00 TEST0001
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25
6
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8
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10
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13
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6
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14
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8
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25
8
25
12
25
6
25
10
25
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25
12
25
9
25
13
25
17
25
13
25
16
25
11
|
24.00 |
|
32.00 |
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40.00 |
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52.00 |
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56.00 |
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32.00 |
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36.00 |
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32.00 |
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48.00 |
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24.00 |
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40.00 |
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36.00 |
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48.00 |
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36.00 |
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52.00 |
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68.00 |
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44.00 |
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0.7664 |
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0.7936 |
0.9527 |
0.8634 |
0.7429 |
0.7380 |
0.7357 |
0.7354 |
0.9018 |
0.7371 |
0.7370 |
0.7399 |
0.7354 |
0.7993 |
0.9223 |
0.8307 |
0.8274 |
0.7355 |
393
1 Examinee675
1.00 TEST0001
1 Examinee676
1.00 TEST0001
1 Examinee677
1.00 TEST0001
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25
10
25
15
25
12
25
13
25
10
25
15
25
6
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14
25
10
25
14
25
13
25
5
25
9
25
16
25
8
25
16
25
13
25
8
25
11
25
10
|
40.00 |
|
60.00 |
|
48.00 |
|
52.00 |
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40.00 |
|
60.00 |
|
24.00 |
|
56.00 |
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40.00 |
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56.00 |
|
52.00 |
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20.00 |
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36.00 |
|
64.00 |
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32.00 |
|
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52.00 |
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32.00 |
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44.00 |
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0.1855
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1.5045
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-1.8089
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-0.1956
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1.5677
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2.3319
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1.1586
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-0.8369
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0.4006
0.7459 |
0.8742 |
0.7375 |
0.7596 |
0.7413 |
0.8466 |
1.2035 |
0.8375 |
0.7415 |
0.8322 |
0.8423 |
0.9311 |
0.7354 |
0.8494 |
0.7434 |
0.9426 |
0.8059 |
0.7573 |
0.7357 |
0.7501 |
394
1 Examinee695
1.00 TEST0001
1 Examinee696
1.00 TEST0001
1 Examinee697
1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
1 Examinee714
1.00 TEST0001
25
14
25
8
25
9
25
11
25
7
25
7
25
13
25
10
25
7
25
10
25
8
25
11
25
11
25
15
25
13
25
14
25
13
25
10
25
14
25
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|
56.00 |
|
32.00 |
|
36.00 |
|
44.00 |
|
28.00 |
|
28.00 |
|
52.00 |
|
40.00 |
|
28.00 |
|
40.00 |
|
32.00 |
|
44.00 |
|
44.00 |
|
60.00 |
|
52.00 |
|
56.00 |
|
52.00 |
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40.00 |
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56.00 |
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36.00 |
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2.3688
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-0.4010
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-0.7900
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-1.9360
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-0.1563
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-0.5066
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-0.4053
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1.8859
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1.7257
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0.8416
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1.6268
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-0.1506
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0.8581
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-0.1479
0.9472 |
0.7373 |
0.7844 |
0.7434 |
0.7663 |
0.8571 |
0.7844 |
0.7373 |
0.7539 |
0.9738 |
0.7354 |
0.7400 |
0.7374 |
0.8871 |
0.8678 |
0.7780 |
0.8562 |
0.7354 |
0.7793 |
0.7355 |
395
1 Examinee715
1.00 TEST0001
1 Examinee716
1.00 TEST0001
1 Examinee717
1.00 TEST0001
1 Examinee718
1.00 TEST0001
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1.00 TEST0001
25
11
25
10
25
10
25
13
25
11
25
11
25
17
25
9
25
11
25
13
25
5
25
12
25
10
25
11
25
11
25
7
25
13
25
14
25
12
25
12
|
44.00 |
|
40.00 |
|
40.00 |
|
52.00 |
|
44.00 |
|
44.00 |
|
68.00 |
|
36.00 |
|
44.00 |
|
52.00 |
|
20.00 |
|
48.00 |
|
40.00 |
|
44.00 |
|
44.00 |
|
28.00 |
|
52.00 |
|
56.00 |
|
48.00 |
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48.00 |
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0.2047
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2.2873
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-0.1058
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0.0834
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-1.6178
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1.0196
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-0.2530
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0.4219
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0.9709
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-0.9436
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1.9651
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0.9389
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0.7521
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0.1197
0.7422 |
0.7440 |
0.7462 |
0.7706 |
0.7716 |
0.7358 |
0.9369 |
0.7505 |
0.7357 |
0.7387 |
0.8774 |
0.7930 |
0.7355 |
0.7511 |
0.7887 |
0.7662 |
0.8968 |
0.7859 |
0.7713 |
0.7396 |
396
1 Examinee735
1.00 TEST0001
1 Examinee736
1.00 TEST0001
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1.00 TEST0001
1 Examinee738
1.00 TEST0001
1 Examinee739
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1.00 TEST0001
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1.00 TEST0001
25
12
25
9
25
13
25
7
25
13
25
9
25
11
25
8
25
12
25
14
25
14
25
11
25
11
25
10
25
9
25
12
25
4
25
12
25
5
25
11
|
48.00 |
|
36.00 |
|
52.00 |
|
28.00 |
|
52.00 |
|
36.00 |
|
44.00 |
|
32.00 |
|
48.00 |
|
56.00 |
|
56.00 |
|
44.00 |
|
44.00 |
|
40.00 |
|
36.00 |
|
48.00 |
|
16.00 |
|
48.00 |
|
20.00 |
|
44.00 |
|
1.1924
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-0.4495
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1.5910
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-1.7241
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0.9314
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0.1460
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-0.2899
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-0.8946
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0.9697
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0.5175
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1.4710
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0.2258
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0.0875
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-1.7588
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-0.1219
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0.5537
|
-3.3131
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0.4728
|
-1.6898
|
-0.0919
0.8092 |
0.7384 |
0.8521 |
0.9058 |
0.7853 |
0.7403 |
0.7358 |
0.7619 |
0.7886 |
0.7562 |
0.8385 |
0.7429 |
0.7388 |
0.9159 |
0.7356 |
0.7582 |
1.9162 |
0.7537 |
0.8963 |
0.7358 |
397
1 Examinee755
1.00 TEST0001
1 Examinee756
1.00 TEST0001
1 Examinee757
1.00 TEST0001
1 Examinee758
1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
25
9
25
13
25
5
25
13
25
11
25
4
25
13
25
9
25
10
25
8
25
8
25
11
25
10
25
6
25
10
25
19
25
14
25
19
25
13
25
11
|
36.00 |
|
52.00 |
|
20.00 |
|
52.00 |
|
44.00 |
|
16.00 |
|
52.00 |
|
36.00 |
|
40.00 |
|
32.00 |
|
32.00 |
|
44.00 |
|
40.00 |
|
24.00 |
|
40.00 |
|
76.00 |
|
56.00 |
|
76.00 |
|
52.00 |
|
44.00 |
|
-1.3690
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0.4287
|
-1.0150
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0.9502
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0.6908
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-2.4463
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1.0338
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-0.6294
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-0.1833
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-0.2814
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-1.3091
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-0.0543
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-0.1519
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-0.6550
|
-0.1960
|
3.4219
|
1.6550
|
4.0000
|
0.3540
|
0.6581
0.8237 |
0.7514 |
0.7733 |
0.7869 |
0.7670 |
1.2095 |
0.7942 |
0.7448 |
0.7354 |
0.7357 |
0.8132 |
0.7362 |
0.7354 |
0.7460 |
0.7354 |
1.0906 |
0.8595 |
999.0000 |
0.7479 |
0.7648 |
398
1 Examinee775
1.00 TEST0001
1 Examinee776
1.00 TEST0001
1 Examinee777
1.00 TEST0001
1 Examinee778
1.00 TEST0001
1 Examinee779
1.00 TEST0001
1 Examinee780
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1 Examinee781
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1 Examinee783
1.00 TEST0001
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25
11
25
12
25
15
25
11
25
14
25
14
25
5
25
10
25
15
25
9
25
4
25
7
25
10
25
14
25
16
25
12
25
14
25
9
25
7
25
12
|
44.00 |
|
48.00 |
|
60.00 |
|
44.00 |
|
56.00 |
|
56.00 |
|
20.00 |
|
40.00 |
|
60.00 |
|
36.00 |
|
16.00 |
|
28.00 |
|
40.00 |
|
56.00 |
|
64.00 |
|
48.00 |
|
56.00 |
|
36.00 |
|
28.00 |
|
48.00 |
|
-0.5115
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0.0586
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1.6912
|
-0.3148
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0.8302
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0.1562
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-3.2307
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0.1360
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1.9031
|
-0.6561
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-3.7463
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-1.0997
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-0.1675
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1.2631
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2.6853
|
0.2484
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0.3324
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0.0197
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-0.9164
|
-0.6458
0.7402 |
0.7382 |
0.8638 |
0.7360 |
0.7771 |
0.7406 |
1.8294 |
0.7401 |
0.8892 |
0.7460 |
2.4448 |
0.7830 |
0.7354 |
0.8163 |
0.9879 |
0.7437 |
0.7470 |
0.7374 |
0.7638 |
0.7455 |
399
1 Examinee795
1.00 TEST0001
1 Examinee796
1.00 TEST0001
1 Examinee797
1.00 TEST0001
1 Examinee798
1.00 TEST0001
1 Examinee799
1.00 TEST0001
1 Examinee800
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1 Examinee802
1.00 TEST0001
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1.00 TEST0001
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1 Examinee806
1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
1 Examinee810
1.00 TEST0001
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1.00 TEST0001
1 Examinee812
1.00 TEST0001
1 Examinee813
1.00 TEST0001
1 Examinee814
1.00 TEST0001
25
9
25
9
25
12
25
9
25
10
25
14
25
12
25
16
25
14
25
14
25
17
25
17
25
17
25
5
25
14
25
14
25
19
25
3
25
15
25
14
|
36.00 |
|
36.00 |
|
48.00 |
|
36.00 |
|
40.00 |
|
56.00 |
|
48.00 |
|
64.00 |
|
56.00 |
|
56.00 |
|
68.00 |
|
68.00 |
|
68.00 |
|
20.00 |
|
56.00 |
|
56.00 |
|
76.00 |
|
12.00 |
|
60.00 |
|
56.00 |
|
-0.4337 0.7380 |
|
-0.7280 0.7500 |
|
0.9548 0.7873 |
|
0.1805 0.7414 |
|
-0.0217 0.7367 |
|
1.7189 0.8670 |
|
-0.2073 0.7354 |
|
2.0657 0.9092 |
|
0.9608 0.7878 |
|
-0.0036 0.7370 |
|
0.8897 0.7819 |
|
2.2645 0.9341 |
|
2.5441 0.9696 |
|
-2.6575 1.3425 |
|
1.7353 0.8690 |
|
1.6578 0.8598 |
|
4.0000 999.0000 |
|
-4.0000 999.0000 |
|
1.2983 0.8200 |
|
1.2917 0.8193 |
400
1 Examinee815
1.00 TEST0001
1 Examinee816
1.00 TEST0001
1 Examinee817
1.00 TEST0001
1 Examinee818
1.00 TEST0001
1 Examinee819
1.00 TEST0001
1 Examinee820
1.00 TEST0001
1 Examinee821
1.00 TEST0001
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1.00 TEST0001
1 Examinee823
1.00 TEST0001
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1.00 TEST0001
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1.00 TEST0001
1 Examinee826
1.00 TEST0001
1 Examinee827
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1 Examinee828
1.00 TEST0001
1 Examinee829
1.00 TEST0001
1 Examinee830
1.00 TEST0001
1 Examinee831
1.00 TEST0001
1 Examinee832
1.00 TEST0001
1 Examinee833
1.00 TEST0001
1 Examinee834
1.00 TEST0001
25
8
25
9
25
2
25
7
25
3
25
3
25
5
25
9
25
7
25
8
25
6
25
6
25
4
25
6
25
5
25
6
25
5
25
3
25
7
25
5
|
32.00 |
|
36.00 |
|
8.00 |
|
28.00 |
|
12.00 |
|
12.00 |
|
20.00 |
|
36.00 |
|
28.00 |
|
32.00 |
|
24.00 |
|
24.00 |
|
16.00 |
|
24.00 |
|
20.00 |
|
24.00 |
|
20.00 |
|
12.00 |
|
28.00 |
|
20.00 |
|
-2.2124 1.0876 |
|
-2.5445 1.2684 |
|
-4.0000 999.0000 |
|
-1.8312 0.9382 |
|
-4.0000 999.0000 |
|
-3.8124 2.5455 |
|
-3.2545 1.8539 |
|
-1.4493 0.8392 |
|
-3.0058 1.6146 |
|
-2.1129 1.0431 |
|
-2.5728 1.2863 |
|
-3.0383 1.6440 |
|
-4.0000 999.0000 |
|
-3.2535 1.8530 |
|
-3.6295 2.2932 |
|
-2.3807 1.1727 |
|
-3.5320 2.1248 |
|
-4.0000 999.0000 |
|
-3.1904 1.7885 |
|
-3.4561 2.0782 |
401
1 Examinee835
1.00 TEST0001
1 Examinee836
1.00 TEST0001
1 Examinee837
1.00 TEST0001
1 Examinee838
1.00 TEST0001
1 Examinee839
1.00 TEST0001
1 Examinee840
1.00 TEST0001
1 Examinee841
1.00 TEST0001
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1.00 TEST0001
1 Examinee843
1.00 TEST0001
1 Examinee844
1.00 TEST0001
1 Examinee845
1.00 TEST0001
1 Examinee846
1.00 TEST0001
1 Examinee847
1.00 TEST0001
1 Examinee848
1.00 TEST0001
1 Examinee849
1.00 TEST0001
1 Examinee850
1.00 TEST0001
1 Examinee851
1.00 TEST0001
1 Examinee852
1.00 TEST0001
1 Examinee853
1.00 TEST0001
1 Examinee854
1.00 TEST0001
25
8
25
10
25
11
25
5
25
4
25
8
25
5
25
5
25
9
25
17
25
17
25
15
25
13
25
12
25
8
25
14
25
10
25
13
25
16
25
11
|
32.00 |
|
40.00 |
|
44.00 |
|
20.00 |
|
16.00 |
|
32.00 |
|
20.00 |
|
20.00 |
|
36.00 |
|
68.00 |
|
68.00 |
|
60.00 |
|
52.00 |
|
48.00 |
|
32.00 |
|
56.00 |
|
40.00 |
|
52.00 |
|
64.00 |
|
44.00 |
|
-1.8401 0.9411 |
|
-1.5357 0.8577 |
|
-1.1488 0.7892 |
|
-2.4285 1.1995 |
|
-4.0000 999.0000 |
|
-1.2276 0.8003 |
|
-2.6081 1.3094 |
|
-2.2147 1.0887 |
|
-0.6295 0.7448 |
|
1.4772 0.8392 |
|
2.1143 0.9152 |
|
2.4292 0.9549 |
|
0.1742 0.7412 |
|
0.6172 0.7621 |
|
-2.0576 1.0202 |
|
0.9314 0.7853 |
|
-0.2389 0.7354 |
|
0.1520 0.7405 |
|
2.7944 1.0022 |
|
-0.6128 0.7440 |
402
1 Examinee855
1.00 TEST0001
1 Examinee856
1.00 TEST0001
1 Examinee857
1.00 TEST0001
1 Examinee858
1.00 TEST0001
1 Examinee859
1.00 TEST0001
1 Examinee860
1.00 TEST0001
1 Examinee861
1.00 TEST0001
1 Examinee862
1.00 TEST0001
1 Examinee863
1.00 TEST0001
1 Examinee864
1.00 TEST0001
1 Examinee865
1.00 TEST0001
1 Examinee866
1.00 TEST0001
1 Examinee867
1.00 TEST0001
1 Examinee868
1.00 TEST0001
1 Examinee869
1.00 TEST0001
1 Examinee870
1.00 TEST0001
1 Examinee871
1.00 TEST0001
1 Examinee872
1.00 TEST0001
1 Examinee873
1.00 TEST0001
1 Examinee874
1.00 TEST0001
25
13
25
11
25
13
25
17
25
12
25
10
25
7
25
12
25
8
25
10
25
14
25
8
25
3
25
5
25
5
25
15
25
10
25
6
25
10
25
9
|
52.00 |
|
44.00 |
|
52.00 |
|
68.00 |
|
48.00 |
|
40.00 |
|
28.00 |
|
48.00 |
|
32.00 |
|
40.00 |
|
56.00 |
|
32.00 |
|
12.00 |
|
20.00 |
|
20.00 |
|
60.00 |
|
40.00 |
|
24.00 |
|
40.00 |
|
36.00 |
|
1.2987
|
0.3784
|
0.0925
|
1.6895
|
0.1544
|
-0.7448
|
-0.7575
|
0.1298
|
-1.1294
|
0.0423
|
1.0954
|
-0.6364
|
-2.6210
|
-1.0586
|
-3.8499
|
0.9933
|
0.4612
|
-1.3151
|
-0.5021
|
0.0019
0.8200 |
0.7490 |
0.7389 |
0.8636 |
0.7406 |
0.7510 |
0.7518 |
0.7399 |
0.7867 |
0.7378 |
0.7999 |
0.7451 |
1.3177 |
0.7781 |
2.5994 |
0.7906 |
0.7531 |
0.8142 |
0.7399 |
0.7371 |
403
1 Examinee875
1.00 TEST0001
1 Examinee876
1.00 TEST0001
1 Examinee877
1.00 TEST0001
1 Examinee878
1.00 TEST0001
1 Examinee879
1.00 TEST0001
1 Examinee880
1.00 TEST0001
1 Examinee881
1.00 TEST0001
1 Examinee882
1.00 TEST0001
1 Examinee883
1.00 TEST0001
1 Examinee884
1.00 TEST0001
1 Examinee885
1.00 TEST0001
1 Examinee886
1.00 TEST0001
1 Examinee887
1.00 TEST0001
1 Examinee888
1.00 TEST0001
1 Examinee889
1.00 TEST0001
1 Examinee890
1.00 TEST0001
1 Examinee891
1.00 TEST0001
1 Examinee892
1.00 TEST0001
1 Examinee893
1.00 TEST0001
1 Examinee894
1.00 TEST0001
25
13
25
9
25
10
25
5
25
13
25
10
25
7
25
5
25
14
25
11
25
9
25
11
25
9
25
7
25
10
25
13
25
14
25
7
25
13
25
10
|
52.00 |
|
36.00 |
|
40.00 |
|
20.00 |
|
52.00 |
|
40.00 |
|
28.00 |
|
20.00 |
|
56.00 |
|
44.00 |
|
36.00 |
|
44.00 |
|
36.00 |
|
28.00 |
|
40.00 |
|
52.00 |
|
56.00 |
|
28.00 |
|
52.00 |
|
40.00 |
|
0.4961
|
-0.1394
|
0.2131
|
-2.8338
|
1.6157
|
0.0476
|
-1.3977
|
-1.8876
|
1.3178
|
0.7011
|
-0.6432
|
0.5626
|
-0.8673
|
-0.7654
|
-0.3802
|
0.4757
|
0.9154
|
-1.4721
|
0.9271
|
-0.3315
0.7550 |
0.7355 |
0.7424 |
1.4715 |
0.8549 |
0.7379 |
0.8290 |
0.9569 |
0.8220 |
0.7677 |
0.7454 |
0.7588 |
0.7596 |
0.7523 |
0.7369 |
0.7539 |
0.7840 |
0.8439 |
0.7850 |
0.7362 |
404
1 Examinee895
1.00 TEST0001
1 Examinee896
1.00 TEST0001
1 Examinee897
1.00 TEST0001
1 Examinee898
1.00 TEST0001
1 Examinee899
1.00 TEST0001
1 Examinee900
1.00 TEST0001
1 Examinee901
1.00 TEST0001
1 Examinee902
1.00 TEST0001
1 Examinee903
1.00 TEST0001
1 Examinee904
1.00 TEST0001
1 Examinee905
1.00 TEST0001
1 Examinee906
1.00 TEST0001
1 Examinee907
1.00 TEST0001
1 Examinee908
1.00 TEST0001
1 Examinee909
1.00 TEST0001
1 Examinee910
1.00 TEST0001
1 Examinee911
1.00 TEST0001
1 Examinee912
1.00 TEST0001
1 Examinee913
1.00 TEST0001
1 Examinee914
1.00 TEST0001
25
12
25
9
25
14
25
13
25
11
25
7
25
8
25
3
25
8
25
13
25
10
25
11
25
10
25
13
25
14
25
10
25
13
25
15
25
16
25
11
|
48.00 |
|
36.00 |
|
56.00 |
|
52.00 |
|
44.00 |
|
28.00 |
|
32.00 |
|
12.00 |
|
32.00 |
|
52.00 |
|
40.00 |
|
44.00 |
|
40.00 |
|
52.00 |
|
56.00 |
|
40.00 |
|
52.00 |
|
60.00 |
|
64.00 |
|
44.00 |
|
0.3518 0.7478 |
|
-0.2421 0.7355 |
|
1.4633 0.8377 |
|
1.2194 0.8119 |
|
-0.5967 0.7433 |
|
-0.6894 0.7478 |
|
-0.7211 0.7495 |
|
-4.0000 999.0000 |
|
-1.0053 0.7723 |
|
0.9271 0.7850 |
|
-0.3499 0.7365 |
|
0.3660 0.7485 |
|
-0.2570 0.7355 |
|
1.4574 0.8370 |
|
1.8149 0.8785 |
|
-0.1303 0.7355 |
|
-0.3065 0.7359 |
|
1.2763 0.8177 |
|
3.2871 1.0705 |
|
0.4116 0.7506 |
405
1 Examinee915
1.00 TEST0001
1 Examinee916
1.00 TEST0001
1 Examinee917
1.00 TEST0001
1 Examinee918
1.00 TEST0001
1 Examinee919
1.00 TEST0001
1 Examinee920
1.00 TEST0001
1 Examinee921
1.00 TEST0001
1 Examinee922
1.00 TEST0001
1 Examinee923
1.00 TEST0001
1 Examinee924
1.00 TEST0001
1 Examinee925
1.00 TEST0001
1 Examinee926
1.00 TEST0001
1 Examinee927
1.00 TEST0001
1 Examinee928
1.00 TEST0001
1 Examinee929
1.00 TEST0001
1 Examinee930
1.00 TEST0001
1 Examinee931
1.00 TEST0001
1 Examinee932
1.00 TEST0001
1 Examinee933
1.00 TEST0001
1 Examinee934
1.00 TEST0001
25
13
25
13
25
3
25
7
25
11
25
13
25
6
25
9
25
8
25
6
25
15
25
15
25
10
25
8
25
9
25
6
25
9
25
17
25
13
25
9
|
52.00 |
|
52.00 |
|
12.00 |
|
28.00 |
|
44.00 |
|
52.00 |
|
24.00 |
|
36.00 |
|
32.00 |
|
24.00 |
|
60.00 |
|
60.00 |
|
40.00 |
|
32.00 |
|
36.00 |
|
24.00 |
|
36.00 |
|
68.00 |
|
52.00 |
|
36.00 |
|
1.0025
|
1.0180
|
-3.0096
|
-1.2813
|
0.2514
|
-0.0982
|
-2.0975
|
-0.2981
|
-1.6008
|
-1.1705
|
1.2450
|
1.6171
|
0.1992
|
-0.4702
|
-1.1208
|
-1.0385
|
-1.8802
|
1.7782
|
1.2642
|
0.6167
0.7914 |
0.7928 |
1.6174 |
0.8086 |
0.7438 |
0.7358 |
1.0365 |
0.7358 |
0.8732 |
0.7921 |
0.8145 |
0.8551 |
0.7420 |
0.7390 |
0.7856 |
0.7759 |
0.9543 |
0.8741 |
0.8164 |
0.7621 |
406
1 Examinee935
1.00 TEST0001
1 Examinee936
1.00 TEST0001
1 Examinee937
1.00 TEST0001
1 Examinee938
1.00 TEST0001
1 Examinee939
1.00 TEST0001
1 Examinee940
1.00 TEST0001
1 Examinee941
1.00 TEST0001
1 Examinee942
1.00 TEST0001
1 Examinee943
1.00 TEST0001
1 Examinee944
1.00 TEST0001
1 Examinee945
1.00 TEST0001
1 Examinee946
1.00 TEST0001
1 Examinee947
1.00 TEST0001
1 Examinee948
1.00 TEST0001
1 Examinee949
1.00 TEST0001
1 Examinee950
1.00 TEST0001
1 Examinee951
1.00 TEST0001
1 Examinee952
1.00 TEST0001
1 Examinee953
1.00 TEST0001
1 Examinee954
1.00 TEST0001
25
12
25
12
25
11
25
8
25
10
25
7
25
16
25
13
25
15
25
12
25
9
25
11
25
15
25
12
25
4
25
14
25
8
25
14
25
14
25
13
|
48.00 |
|
48.00 |
|
44.00 |
|
32.00 |
|
40.00 |
|
28.00 |
|
64.00 |
|
52.00 |
|
60.00 |
|
48.00 |
|
36.00 |
|
44.00 |
|
60.00 |
|
48.00 |
|
16.00 |
|
56.00 |
|
32.00 |
|
56.00 |
|
56.00 |
|
52.00 |
|
0.4677
|
0.2713
|
-0.0462
|
-0.4907
|
-0.2477
|
-1.7398
|
2.7350
|
0.6678
|
1.3256
|
1.2422
|
-0.7979
|
0.6278
|
1.2087
|
0.8730
|
-1.4519
|
1.9090
|
-0.7709
|
1.0844
|
1.5935
|
1.1248
0.7534 |
0.7445 |
0.7363 |
0.7395 |
0.7355 |
0.9103 |
0.9943 |
0.7654 |
0.8228 |
0.8142 |
0.7545 |
0.7628 |
0.8108 |
0.7805 |
0.8397 |
0.8899 |
0.7526 |
0.7989 |
0.8524 |
0.8027 |
407
1 Examinee955
1.00 TEST0001
1 Examinee956
1.00 TEST0001
1 Examinee957
1.00 TEST0001
1 Examinee958
1.00 TEST0001
1 Examinee959
1.00 TEST0001
1 Examinee960
1.00 TEST0001
1 Examinee961
1.00 TEST0001
1 Examinee962
1.00 TEST0001
1 Examinee963
1.00 TEST0001
1 Examinee964
1.00 TEST0001
1 Examinee965
1.00 TEST0001
1 Examinee966
1.00 TEST0001
1 Examinee967
1.00 TEST0001
1 Examinee968
1.00 TEST0001
1 Examinee969
1.00 TEST0001
1 Examinee970
1.00 TEST0001
1 Examinee971
1.00 TEST0001
1 Examinee972
1.00 TEST0001
1 Examinee973
1.00 TEST0001
1 Examinee974
1.00 TEST0001
25
10
25
12
25
13
25
6
25
9
25
6
25
8
25
16
25
7
25
6
25
12
25
13
25
13
25
10
25
12
25
13
25
10
25
10
25
10
25
10
|
40.00 |
|
48.00 |
|
52.00 |
|
24.00 |
|
36.00 |
|
24.00 |
|
32.00 |
|
64.00 |
|
28.00 |
|
24.00 |
|
48.00 |
|
52.00 |
|
52.00 |
|
40.00 |
|
48.00 |
|
52.00 |
|
40.00 |
|
40.00 |
|
40.00 |
|
40.00 |
|
-1.2469
|
0.7812
|
0.8620
|
-1.1804
|
0.1204
|
-1.1208
|
-0.6018
|
1.6953
|
-0.8837
|
-3.4867
|
-0.2894
|
0.9898
|
0.8144
|
-0.2757
|
0.8019
|
0.6029
|
0.5260
|
0.2782
|
-0.4830
|
-0.7835
0.8032 |
0.7734 |
0.7796 |
0.7935 |
0.7396 |
0.7856 |
0.7435 |
0.8642 |
0.7610 |
2.1144 |
0.7358 |
0.7903 |
0.7759 |
0.7356 |
0.7750 |
0.7612 |
0.7566 |
0.7448 |
0.7393 |
0.7535 |
408
1 Examinee975
1.00 TEST0001
1 Examinee976
1.00 TEST0001
1 Examinee977
1.00 TEST0001
1 Examinee978
1.00 TEST0001
1 Examinee979
1.00 TEST0001
1 Examinee980
1.00 TEST0001
1 Examinee981
1.00 TEST0001
1 Examinee982
1.00 TEST0001
1 Examinee983
1.00 TEST0001
1 Examinee984
1.00 TEST0001
1 Examinee985
1.00 TEST0001
1 Examinee986
1.00 TEST0001
1 Examinee987
1.00 TEST0001
1 Examinee988
1.00 TEST0001
1 Examinee989
1.00 TEST0001
1 Examinee990
1.00 TEST0001
1 Examinee991
1.00 TEST0001
1 Examinee992
1.00 TEST0001
1 Examinee993
1.00 TEST0001
1 Examinee994
1.00 TEST0001
25
10
25
9
25
10
25
11
25
11
25
10
25
9
25
9
25
10
25
8
25
11
25
14
25
10
25
13
25
12
25
8
25
16
25
13
25
7
25
14
|
40.00 |
|
36.00 |
|
40.00 |
|
44.00 |
|
44.00 |
|
40.00 |
|
36.00 |
|
36.00 |
|
40.00 |
|
32.00 |
|
44.00 |
|
56.00 |
|
40.00 |
|
52.00 |
|
48.00 |
|
32.00 |
|
64.00 |
|
52.00 |
|
28.00 |
|
56.00 |
|
-0.0653
|
0.2351
|
0.4459
|
0.1910
|
-0.0980
|
-0.0196
|
-0.5933
|
-0.8895
|
0.0964
|
-0.2521
|
1.0487
|
1.0673
|
-0.3811
|
0.9704
|
0.4056
|
-0.9731
|
1.7260
|
0.4953
|
-0.6908
|
0.7896
0.7361 |
0.7432 |
0.7523 |
0.7417 |
0.7358 |
0.7367 |
0.7432 |
0.7615 |
0.7390 |
0.7355 |
0.7956 |
0.7973 |
0.7370 |
0.7886 |
0.7503 |
0.7691 |
0.8679 |
0.7549 |
0.7479 |
0.7740 |
409
1 Examinee995
|
|
1.00 TEST0001 25 14 56.00 | 1.0226 0.7932 |
1 Examinee996
|
|
1.00 TEST0001 25 14 56.00 | 1.1665 0.8067 |
1 Examinee997
|
|
1.00 TEST0001 25 12 48.00 | 0.7999 0.7748 |
1 Examinee998
|
|
1.00 TEST0001 25
9 36.00 | -0.9544 0.7672 |
1 Examinee999
|
|
1.00 TEST0001 25 16 64.00 | 2.3418 0.9438 |
----------------------------------------------------------------
======================================
TEST0001
TEST0001
1.0000
TEST:
TEST0001
MEAN:
0.0605
S.D.:
1.2660
VARIANCE:
1.6028
ESTIMATES
TEST:
TEST0001
RMS:
0.7962
VARIANCE:
0.6339
410
EMPIRICAL
RELIABILITY:
0.6045
IN PHASE-3
IN PHASE-3
3PM BILOG CURVES
Item Characteristic Curv e: ITE M0001
a = 0.829
b = -0.904
Item Information Curv e: ITE M0001
c = 0.107
0.5
0.8
0.4
0.6
0.3
Probability
Information
1.0
0.4
0.2
c
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
3-P arameter Model, Logistic Metric
0
1
2
3
Scale Score
Item: 1
411
Item Characteristic Curv e: ITEM0002
a = 0.605
b = 0.800
Item Information Curv e: ITEM0002
c = 0.141
0.5
0.8
0.4
0.6
0.3
P robability
Information
1.0
0.4
0.2
c
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 2
412
a = 0.770
b = -0.200
c = 0.097
0.5
0.8
0.4
0.6
0.3
P robability
Inform ation
1.0
0.2
0.4
c
0.1
0.2
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 3
413
a = 0.775
b = -0.061
c = 0.123
0.5
0.8
0.4
0.6
0.3
P robability
Inform ation
1.0
0.2
0.4
c
0.1
0.2
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 4
414
a = 0.539
b = 1.139
c = 0.157
0.5
0.8
0.4
0.6
0.3
P roba bilit y
Inf orm a t ion
1.0
0.4
0.2
c
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 5
415
a = 1.377
b = -1.257
c = 0.080
0.5
0.8
0.4
0.6
0.3
P robability
Inform ation
1.0
0.4
0.2
0.2 c
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 6
416
a = 0.979
b = 0.123
c = 0.079
0.5
0.8
0.4
0.6
0.3
P roba bilit y
Inf orm a t ion
1.0
0.4
0.2
0.2 c
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 7
417
a = 1.014
b = -0.875
c = 0.087
0.5
0.8
0.4
0.6
0.3
P robability
Inform ation
1.0
0.2
0.4
0.2
c
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 8
418
a = 0.985
b = 0.772
c = 0.067
0.5
0.8
0.4
0.6
0.3
P rob a b ilit y
Inf orm a t ion
1.0
0.4
0.2
0.2 c
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 9
419
a = 0.913
b = -0.089
c = 0.089
0.5
0.8
0.4
0.6
0.3
P ro ba bilit y
Inf o rm a t ion
1.0
0.4
0.2
0.2
c
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 10
420
a = 0.307
b = 5.033
c = 0.105
0.5
0.8
0.4
0.6
0.3
P robability
Inform ation
1.0
0.2
0.4
c
0.1
0.2
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 11
421
a = 0.917
b = 0.154
c = 0.078
0.5
0.8
0.4
0.6
0.3
P roba bilit y
Inf orm a t ion
1.0
0.4
0.2
0.2 c
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 12
422
a = 0.407
b = 1.203
c = 0.186
0.5
0.8
0.4
0.6
0.3
P ro b a b ilit y
In f o rm a t io n
1.0
0.4
0.2
c
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 13
423
a = 0.677
b = -1.443
c = 0.118
0.5
0.8
0.4
0.6
0.3
P robability
Inform ation
1.0
0.2
0.4
c
0.1
0.2
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 14
424
a = 0.494
b = 4.440
c = 0.098
0.5
0.8
0.4
0.6
0.3
P robability
Inform ation
1.0
0.4
0.2
c
0.2
0
-3
0.1
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 15
425
a = 0.345
b = 5.514
c = 0.090
0.5
0.8
0.4
0.6
0.3
P roba bilit y
Inf orm a t ion
1.0
0.2
0.4
0.2
0
-3
c
0.1
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 16
426
a = 0.304
b = 4.808
c = 0.113
0.5
0.8
0.4
0.6
0.3
P robability
Inform ation
1.0
0.4
0.2
c
0.2
0
-3
0.1
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 17
427
a = 0.324
b = 2.534
c = 0.133
0.5
0.8
0.4
0.6
0.3
P roba bilit y
Inf orm a t ion
1.0
0.4
0.2
c
0.2
0.1
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 18
428
a = 0.648
b = 3.291
c = 0.184
0.5
0.8
0.4
0.6
0.3
P r o b a b ilit y
In f o r m a t io n
1.0
0.2
0.4
c
0.1
0.2
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 19
429
Item Characteristic Curv e: ITE M0020
a = 0.254
b = 5.805
c = 0.105
0.5
0.8
0.4
0.6
0.3
Probability
Information
1.0
0.2
0.4
c
0.1
0.2
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 20
430
a = 0.973
b = 2.872
c = 0.225
0.5
0.8
0.4
0.6
0.3
P robability
Inform a t ion
1.0
0.2
0.4
c
0.1
0.2
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 21
431
a = 0.550
b = 1.832
c = 0.130
0.5
0.8
0.4
0.6
0.3
Probability
Information
1.0
0.2
0.4
c
0.1
0.2
b
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 22
432
a = 0.364
b = 6.116
c = 0.110
0.5
0.8
0.4
0.6
0.3
P ro b a b ilit y
In f o rm a t io n
1.0
0.4
0.2
c
0.2
0
-3
0.1
-2
-1
0
1
2
3
0
-3
-2
-1
Ability
0
1
2
3
Scale Score
Item: 23
433
a = 0.411
b = 4.718
c = 0.138
0.5
0.8
0.4
0.6
0.3
P robability
Inform ation
1.0
0.2
0.4
c
0.1
0.2
0
-3
-2
-1
0
1
2
3
0
-3
-2
-1
0
1
2
3
Scale Score
Ability
Item: 24
Application of IRT to Item Banking
It was indicated earlier that one of the most important applications of IRT is in the domain of
item banking. HMSO definition of question banking/item banking is as follows:
“A bank of items (questions) of known technical values can be built up for future
use. It might, in practice, prove of value to arrange for item construction to be a
more or less continuous process. The construction of written papers can then
become a matter of judging the suitability of items of known technical values
from a bank of items. Items can be weeded out as out of date over a period of
time. Further it can be said that new questions should be tried out and statistical
evidences for its facility, discrimination ascertained it is absolutely necessary that
the banks would have to be large to be of value".
434
This definition is a universally adopted one and in order to apply this to the MeritTrac item
bank (that is already available) will involve:
1. Examining and pre-validating all the individual items in the bank in several domains
to check content and format accuracy. The procedure for pre-validation is explained
below:
Pre-validation is a process by which a judgment is made about an individual item
with respect to satisfying certain criteria both looking at content and format
accuracy. A checklist of criteria is given below in terms of general and specific
criteria for multiple choice items and similarly for other types:
General
Is the item measuring an important outcome or objective agreed to be included
in the test?
Is the item measuring an important content area or expansion of content area?
Is the item pitched at an acceptable difficulty level (0.1 to 0.9)?
Is the item capable of being answered right by a majority of more able and more
proficient test takers (HAG)?
Is the item likely to be answered wrong by a majority of less able and less
proficient test takers (LAG)?
Is the item capable of restructuring?
Does the item have one and only one correct answer?
Specific

Is the stem clear and unambiguous for a majority of test takers?
Is the stem devoid of double negatives?
If a single negative is unavoidable, does it get highlighted in the stem?
Are the distractors plausible ie the usual mistakes, misconceptions and
misunderstandings?
Is the key unarguably and unequivocally correct?
If there are multiple answers, does the format take this into account?
Is the item using an efficient format?
Does the item avoid “window dressing”?
At the end of applying this checklist for every individual item, a decision whether to
include item in the bank, reject the item or improve the item to include in the bank,
shall be taken.
2. Once an item is decided to be included in the bank there are some technical values
to be added to the item. Some of these are:
435
Content ID
This is coded as C1, C11, C12 and so on. It indicates the major content topic and
sub topics that are expansions of the content.
Ability/Skill Tested ID
This is coded as A1, A2, A3 and so on that are clusters of Bloom Level
Objectives/outcomes; for instance A1 may include Knowledge (recall),
Comprehension (interpret, detect mistakes), Application (solve, predict)
and Evaluation (judge) etc. A1 KCAE.
Item ID
A combination of content/ability/difficulty; for instance C11 A1 KCAE d001,
the last digits gives the number of identify. In content C11, we may have
C11 A1 KC d2 004 or C11 A1 KCA d3 003 or C11 A1 KCAE d4 005 and so
on.
Item Writer ID
It is the code given by MeritTrac to every item writer.
Difficulty Level
Difficulty levels are d1, d2, d3, d4, d5.
d1 – 0 to 0.2
Very Easy
d2 – 0.2 to 0.4
Easy
d3 – 0.4 to 0.6
Average
d4 – 0.6 to 0.8
Difficult
d5 – 0.8 to 1.0
Very Difficult
Time for answering
This is invariably decided by the item writer. If it is a simple MC item it can be 1
min, if the stem is lengthy as in the case of a passage or data, time will be
decided accordingly.
Correct or key answer
This should be hidden from the bank.
Type of Item
MC1 – Multiple Choice 1 in n (n=3, 4 or 5)
MC2 – Multiple Completion (multiple answers combination)
MC3 – Multiple T/F
MC4 – Multiple Facet (a no. of MC items in a topic together)
MC5 – Assertion Reason
Allotted Marks
Marks are to be allotted for the right answer. Invariably 1 mark is to be
allotted. If scoring weight is available as a result of a large number of test
takers in the past and if CTT analysis is done earlier then the scoring weight can
be indicated. The index of difficulty and scoring weights may be given. If IRT
analysis has been done earlier using any of the three models (preferably a Two
Parameter model to start with and then graduated to Three Parameter model
later) then the item difficulty and scoring weights correspondingly may be
added.
436
An illustrative example in C++ is shown below:
Merittrac’s Current 2-Dimensional Template
C++ Test Outline
Classification Of Topics
Debugging Skills / Implementing OOPS in
C++
Questions of Each Difficulty Level
2
3
4
1
Total
1
Debugging Skills / Pointers
1
1
Logic / Files & Streams
3
3
2
4
Logic / Implementing OOPS in C++
2
2
Logic / User Defined Datatypes
1
1
Programming Concepts / Files & Streams
1
1
Logic / Fundamentals
Programming Concepts / Friend Functions
& Classes
2
1
1
437
Programming Concepts / Fundamentals
4
Programming Concepts / Implementing
OOPS in C++
2
1
3
Programming Concepts / Late Binding
2
1
3
1
1
Programming Concepts / User Defined
Datatypes
4
Software / Advanced C Programming /
Debugging Skills / Templates
1
1
Logic / Templates
1
3
4
Programming Concepts / Exceptions
3
3
6
2
2
4
40
Programming Concepts / Templates
Total (No of Questions)
Total Time in Minutes
45
Modified Content Template
Content
C1
Debugging
C2
Logic
C3
Programming
C4
Software &
Advanced
Programming
Content Expansion
C11 - Implementing
OOPS
C12 - Skills & Pointers
C21 - Files & Streams
C22 - Fundamentals
C23 - User Defined
Datatypes
C24 - Implementing
OOPS
C31 - Files & Streams
C32 - Friend Functions &
Classes
C33 - Fundamentals
C34 - Implementing
OOPS
C35 - Late Binding
C36 - User Defined
Datatypes
C41 - Debugging Skills &
Templates
C42 - Logic & Templates
C43 - Programming
Concepts & Exceptions
Ability
Cluster
A1 - KCE
A2 – KCAn
A3 – KCApE
A4 - KCAp
Difficulty Level
KC – d2 (easy)
KCE – d3 (average)
No. of
Items
1
1
KC E- d3
KC – d2
KCAn – d3
KC– d2
KCAn – d3
3
2
2
1
KCAp– d3 (difficult)
KC – d2
KC – d2
KC – d2
KCApE – d3
KC – d2
KCApE – d3
KCApE – d3
1
1
4
2
1
2
1
KCAp – d4
KC – d3
KCAp d4
KC – d3
KCAp – d4
1
1
3
3
3
Total
2
10
2
13
1
15
438
C44 - Programming
Concepts & Templates
•
•
•
•
•
•
KC – d3
KCAp – d4
2
2
A1 – KCE means Knowledge Comprehension Evaluation (a simple judgment).
A2 – KCAn means Knowledge Comprehension Analysis
A3 – KCApE means Knowledge Comprehension Application Evaluation
d2 – easy
d3 – average
d4 – difficult
It is evident from the above that in the case of existing item bank, the
present
2Dimensional content template can be modified and used to add
Item ID to every individual
item. Item IDs used for C++ are given below:
Sample Paper
Duration in minutes:40
Item No
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Q10
Q11
Q12
Q13
Q14
Q15
Q16
Q17
Q18
Q19
Q20
Q21
Q22
No of Question:40
Section 1 - C++ Programming
Item ID
C23A2KCEd1001
C23A2KCEd1002
C32A3Kd1003
C32A3Kd1004
C32A3KEd1005
C32A3Kd1006
C32A3KCEd1007
C33A3KCEd1008
C33A3Kd1009
C33A3KCEd1010
C34A3KCEd1011
C31A3KCAd2012
C31A3KCAd2013
C31A3KCAd2014
C32A3KCAd2015
C32A3KCAd3016
C32A3KCAd2017
C36A3KCAd2018
C36A3KCAd2019
C36A3KCAd2020
C11A1KCAd4021
C32A3Kd4022
439
Application of IRT to Adaptive or Tailored Testing
A very significant application of IRT is in the area of adaptive or tailored testing. For decades,
attempts have been made to introduce adaptive or tailored testing out of necessity to reduce
the number of test items and at the same time increase the accuracy of measurement. It is
imperative that clients who are increasingly demanding a shorter duration test and a more
accurate measurement and assessment will increasingly accept adaptive or tailored testing
modules. It should be noted here that there are some pre-requisites before an adaptive testing
module is designed. The first step is therefore to have a sufficiently large bank of items and
administered over a fairly large population of test takers. The number of items in the bank
may not be of the same number of items that we store in a normal item bank used for
creating a paper and pencil test. For instance, if the analytical ability test has at the moment
25 items, the normal item bank should have a minimum of 15 times this number when it is
used for creating paper and pencil tests. But, for adaptive testing module the item bank can
be anything up to 10 times. However, the calibration of these items using IRT in adopting any
of the three models is to be initially done for a population of test takers (anything between
200 to 500 test takers).
The adaptive testing module will thus normally have 200 items distributed over desired
contents and with the help of 3-d building block blueprint these items after administration will
be analyzed through any of the models and the item parameters (1, 2 or 3) shall be
ascertained. Also the ICCs and item information function curves will be plotted and stored with
preferably test characteristics curve and test information function. Then the parent test is
ready for use. Once this is done the module is ready for use. All the calibrated items in the
bank are to be re-arranged in terms of increasing difficulty. Then it is possible to administer an
adaptive test to test takers individually and ascertain their true score by finding the true ability
and calculating true score as if he has taken the parent test.
A test taker now can be administered with an item selected on the basis of an assumption
relating to his ability. This is invariably his/her own judgment about his ability indicated by his
position on the Z scale (-3 to +3) or on a scaled score available to him by way of standard
scales like TOEFL, GRE, GMAT etc. The reader may refer to Rudner’s Computer Adaptive
Testing tutorial that is attached to the appendix of this book.
This is an interesting and self learning computer adaptive testing tutorial meant for testing an
average level of arithmetic ability with a bank of 200 items. A test taker is shown the first item
matched to the difficulty level at the ability of a test taker that is judged by himself/herself.
Once the test taker answers it correctly it automatically goes to the next item which is of a
440
higher difficulty than the first item. In case he answers this item also correctly the process is
repeated till the test taker answers an item wrong. This is where the test can be terminated.
There are several rules for termination as stated below out of which any one can be adopted
according to convenience:
•
•
•
The time at the disposal of test taker and administrator
By a fixed number of items like 5 to 10
Till a consistent estimate of his ability at successive trials during the process. The final
ability of the test taker is determined and a corresponding true score can be determined
taking this final ability estimate and applying it over all the items in the parent test.
Thus a replacement of the parent test is done by a short duration adaptive testing
module having a very small number of items.
Illustrations
1. A test of 5 items administered on 10 test takers is converted into an adaptive or
tailored testing module. At this stage a test taker X will be assumed to have taken 2
items namely 5 and 2 and his response pattern is Correct & Incorrect. The test is
terminated at this point. An ability estimate can be made working out an initial
estimate of 0.3 since item #5 and #2 have difficulty values of -0.28 and 0.42
respectively.
Test Taker X taking an Adaptive Test with 2 Items (Item #5, #2)
Item
No
B
U
5
0.28
1
2
0.42
0
Item
No
B
U
5
0.28
1
2
0.42
0
p=1/(1+e(θ-b)
)
q=1p
0.560
0.641
0.359
1.127
0.470
0.530
θ
-(θb)
e-(θ-
0.3
-0.58
0.12
b)
p=1/(1+e(θ-b)
)
q=1p
0.652
0.605
0.395
1.313
0.432
0.568
θ
-(θb)
e-(θ-
0.15
-0.43
0.27
b)
u-p
p*q
0.359
0.470
0.111
0.230
Correction
Next
Factor
Estimate
-0.152
0.148
0.502
0.732
u-p
p*q
0.395
0.432
0.038
0.239
Correction
Next
Factor
Estimate
-0.078
0.070
0.245
0.484
441
Item
No
B
U
θ
-(θb)
5
0.28
1
0.07
0.350
2
0.42
0
0.350
p=1/(1+e(θ-b)
)
q=1p
0.705
0.587
0.413
1.419
0.413
0.587
e-(θb)
u-p
p*q
0.413
0.413
0.000
0.242
Correction
Next
Factor
Estimate
0.000
0.070
0.242
0.485
Let us take another test taker Y who is assumed to have taken the items #4, #1 &
#3. The response pattern is Correct, Correct and Incorrect. The
test is terminated at this
point. The final ability can be estimated by using
an initial estimate of 1.5. This
assumption is made on the basis that he
answered item #4 correct with difficulty value
of 0.92 and also answered item #1 correct with difficulty value of 1.5. He answered item #3
incorrect
with difficulty value of 2.29. His final estimate is worked out as follows:
Test Taker X taking an Adaptive Test with 3 Items (Item #4, #1,#3)
p=1/(1+e(θ-b)
)
q=1p
0.560
1.000
0.641
0.500
0.359
0.500
0.79
2.203
0.312
0.688
-(θb)
e-(θ-
p=1/(1+e(θ-b)
)
q=1p
-1.37
-0.79
0.255
0.455
0.797
0.687
0.203
0.313
-(θb)
e-(θ-
-0.58
0.00
0
Item
No
b
U
θ
4
1
0.92
1.50
1
1
1.5
3
2.29
b)
Item
No
b
U
θ
4
1
0.92
1.50
1
1
2.287
3
2.29
0
0.00
1.003
0.499
0.501
-(θb)
e-(θ-
p=1/(1+e(θ-b)
)
q=1p
-1.39
-0.81
0.248
0.443
0.801
0.693
0.199
0.307
-0.02
0.976
0.506
0.494
Item
No
b
U
θ
4
1
0.92
1.50
1
1
2.314
3
2.29
0
b)
b)
u-p
p*q
0.359
0.500
0.312
0.547
0.230
0.250
0.215
0.695
u-p
p*q
0.203
0.313
0.499
0.017
0.162
0.215
0.250
0.627
u-p
p*q
0.199
0.307
0.506
0.000
0.159
0.213
Correction
Factor
Next
Estimate
0.787
2.287
Correction
Factor
Next
Estimate
0.027
2.314
Correction
Factor
Next
Estimate
0.000
2.314
0.250
0.622
442
Thus, the ability of the test taker X and that of test taker Y are calculated as 0.070 and 2.314
respectively after administering the adaptive test to them. Their true scores can be calculated
by taking these final ability values to the parent test of 5 items. The calculations are shown
below:
Calculation of True Scores of Test Takers X & Y
Ability
Test Taker
X
Test Taker
Y
True
Score
Item 1
Item2
b value
Item3
1.5
0.42
2.29
0.92
-0.28
0.07
0.193099
0.443517
0.136286
0.31352
0.644172
1.73059428
2.314
0.692961
0.56782
0.151591
0.316823
0.644929
2.374123965
Item4
Item5
2. An Analytical Ability test of 25 items administered on 1000 test takers. This is our
parent test and calibration is done on this test. The initial IRT calibration is done and
the ICCs of all the items are plotted and stored. A program segment will re-arrange
the item difficulty values of these items in an ascending order and keep it ready for
administering an adaptive test. For any test taker, his initial ability is assumed and
accordingly an item easier than his own ability indicator is administered. The process
of choosing more difficult items successively will be continued till he answers any one
or two items incorrect. The test can be terminated at this point and the ability
estimated as indicated above. For details of this sample click the following hyperlinks:
•
Introduction
443
Analytical Ability Adaptive Test Module
Introduction
The Analytical Ability Test (Set : 1675 ver 1.0) of 25 items on a total population of 1000 test
takers is taken for purposes of creating an adaptive test manual for future use. It’s imperative
that the test response data should be analyzed through BILOG to generate outputs like
Phase1, Phase2 & Phase3 together with a plot of Item Characteristics Curves (ICC). To
constitute an adaptive test module the pre-requisites are:
1. A modified and re-arranged Ph2 giving item difficulty values with increasing difficulty
values which will form the order in which the items will be administered in the adaptive
test module to future test takers.
2. A set of ICC (Item Response Function together with Item Information Function for all
the 25 items).
3. A program module which will enable registration details of a test taker and an initial
assumption on his ability to give a starting point. The program module should also
make a choice of the first item to be administered in accordance with the assumption
made. The response of the test taker to this initial item is registered with a decision of
right or wrong answer. If the answer is right, an initial first estimate of his ability is
made as indicated in this forthcoming article. The next item to be administered to the
same test taker is to be chosen as the next more difficult item. And the response again
registered. If the response is again correct, proceed further with successive items with
increasing difficulty values. The test will be terminated at an item for which the
response is incorrect. The final estimate of his ability is arrived at successively.
A test characteristic curve giving ability and true scores as two parameters is already
available and this can be used to infer the estimated true score for the final estimate of
the ability of the test taker.
•
Question Paper
3. Set: 1675 ver 1.0
4.
5. Section 1 - Analytical Ability
No of Questions: 25
Duration in Minutes: 30
6.
7. 1) During a visit to a foreign country, delegates to a seminar found communication among themselves to
be a big problem. In a group of 1000 delegates, 250 could speak only English and 600 could speak only
French. How many delegates could speak French in the group?
8.
9. A) 1000
B) 750
C) 600
D) 250
444
10.
11.
2) In a survey conducted among some friends attending a school re-union, it was found that 10 friends
still met for movies, 20 friends met for picnics and 5 friends met for games. 4 friends met for movies and
picnics but not for games while 2 met for movies and games but not for picnic. None of the friends met
for picnics and games. 2 friends met for movies, picnics and games. How many students participated in
the survey?
12. A) 11
13.
D) 35
B) 16
C) 25
3) At an international conference, 100 delegates spoke English, 40 spoke French, and 20 spoke both
English and French. How many delegates could speak at least one of these two languages?
14.
15. A) 110
D) 120
B) 100
C) 140
4) A restaurant has a bar and a separate section for teetotalers. Moreover, smokers can visit the bar but
not the area for teetotalers. On a particular day, some drinkers, smokers and teetotalers visit the
restaurant. Out of the 2500 guests, 1600 were drinkers, 1250 were smokers and 750 were smokers and
drinkers. Find the number of teetotalers who were present.
16.
17. A) 300
B) 350
C) 400
D) 450
18.
5) On a particular day in a restaurant, 2/3 of the regular customers had lunch, 12 had dinner and 10
customers had both lunch and dinner while 6 did not have either lunch or dinner but visited the
restaurant with friends. How many customers visited the place?
19.
20. A) 6
B) 12
C) 24
D) 36
21.
22. Directions for Questions 6-9:
23.
24. 6 couples are meeting at a dinner. The husbands are A, B, C, D, E and F. The wives are P, Q, R, S, T and
U, but not necessarily in that order. B is married to Q but he is neither an engineer nor a computer
professional. R’s husband is not an architect. F is not a doctor. C is not married to R, S or U. P’s
husband is a computer professional. A, C and D are an engineer, architect or lawyer. U’s husband is a
doctor. One of the men is a chartered accountant.
25.
6) Who is married to C?
26. A) R
B) S
27.
7) Who is the chartered accountant?
28.
29. A) A
B) B
30.
8) Who is U’s husband?
31.
32. A) B
B) C
33.
9) Who is F’s wife?
34.
35. A) P
B) Q
36.
C) T
D) U
C) D
D) F
C) E
D) F
C) R
D) T
445
37.
38.
39.
40.
42.
43. Follow the directions given below to answer the questions that follow
Your answer for each question below would be
1, if the question can be answered with the help of statement I alone.
2, if the question can be answered with the help of statement II alone.
3, if the question can be answered with the help of both statement I and II, but not with the help of
either of them independently.
4, if the question cannot be answered at all.
44.
45. 10) A chemical composition contains only chemical A and chemical B. What is the ratio of the two
chemicals?
46.
47. I. 2.2 grams of chemical A is present in x kilogram of the composition.
48. II. 1.3 grams of chemical A is present in 2kilograms of the composition.
49.
50. A) 1
B) 2
C) 3
D) 4
51.
52.
11) Sarthak is a worker in a factory and is required to pack balls in a container. At
what time did he finish the assigned work on a particular day?
53.
I. He started work at 8 am.
II. By 9.30 am, he had done half the work and by 10.10 am, he had done 5/6th of the
work.
54.
55. A) 1
56.
B) 2
C) 3
D) 4
57.
12) Did the price of wheat increase by more than 5% last year?
58.
I. The production of wheat increased by 5%.
II. Wheat exports increased by 10%.
59.
60. A) 1
B) 2
61.
62. 13) Manish is friendly. Is Manish a joker?
63.
64. I. All graduates are friendly
65. II. No graduate is a joker.
66.
67. A) 1
B) 2
68.
C) 3
D) 4
C) 3
D) 4
446
69. 14) What is the value of (A + B)?
70.
71. I. A = 1 + 3 + 5 + …. + 17
72. II. B = 9 + 11 + …. + 17
73.
74. A) 1
B) 2
75.
C) 3
D) 4
76.
15) Pipe A takes 3 minutes longer to fill a bucket than pipe B does. It would take
them 6 minutes 40 seconds to fill the bucket together. How much time will it take for
pipe B to fill the bucket?
77.
78. A) 3 minutes
B) 6 minutes
C) 10 minutes
D) 12
minutes
79.
81.
82. In a certain code, the symbol for 0 (zero) is * and that for 1 is $. The numbers greater than 1 are to be
written only by using the two symbols given above. The value of the symbol for 1 doubles itself every
time it shifts one place to the left (for example, 4 is written as $*; and; 3 is written as $$)
83.
84.
85.
16) The LCM of 23, 32, and 55 is represented as:
86. A) $*$*$*
$**$$$$***$*****
B) $$**$$*$*
C) $*$*$*$*$*$*
D)
87.
88. 17) The value of
89. (9^2 – 2^2) + (8^2 – 3 ^2) + (7^2 – 4^2) is represented as:
90.
91. Replace ^ with raised to power.
92.
93. A) $$**$$**
B) $*$**$*$
$**$**$$
94.
95.
96.
C) $*$*$*$*
D)
18) The product of ($$*$*) and ($**$**) is represented as :
97. A) $$$***$$
B) $$**$$**$$
$*$*$*$*$*
98.
19) The number 345 is represented as:
99.
100.
A) $$**$$**$
B) $*$*$$**$
D) $****$$$$
101.
102.
103.
20) The value of 7x10-2x3-3x4-4x5-5x6 is
104.
A) $*
D) $$**$
B) $$*
C) $$$*$*$***
D)
C) $*****$$$
C) $*$*
447
105.
106.
Directions for Questions 21-25:
107.
108.
During a visit through a national sanctuary, 8 tourists are seated in 2 jeeps. Each jeep has 2 seats in
the front and 2 behind them. After every one hour, the jeeps are stopped and the tourists change their
seats so that every one has a view of all sides. The tourists Jay, Kim, Laine, Mary, Neil, Oliver, Pam and
Quiver must follow the following instructions. The tourist who acts as a guide on the trip must always
sit on the left side of the front seat. Quiver and Pam cannot sit in the same jeep. Jay must sit directly
behind Neil in the same jeep.
109.
110.
21) If Kim sits on the front in one jeep with Quiver as the guide, and Oliver is the
guide for the other jeep, all of the following must be true except:
111.
112.
A) Oliver sits in front of Pam
113.
B) Quiver sits in front of Laine
114.
C) Pam sits next to Jay
115.
D) Mary sits next to Laine
116.
22) If Pam sits behind Oliver and Quiver sits next to Mary, which of the following must be TRUE?
117.
118.
A) Kim sits behind Quiver
119.
B) Laine sits behind Mary
120.
C) Kim sits next to Laine
121.
D) Jay sits next to Kim
122.
23) If Kim sits behind Pam in a jeep, in which Mary is the guide, then all of the following could be true
except:
123.
124.
A) Laine sits next to Oliver
125.
B) Oliver sits next to Jay
126.
C) Oliver sits next to Neil
127.
D) Laine sits behind Mary
128.
24) If Kim and Mary are the two guides, then which of the following must be TRUE?
129.
130.
A) Laine sits next to either Kim or Oliver
131.
B) Jay sits next to either Pam or Quiver
132.
C) Kim sits next to either Laine or Oliver
133.
D) Oliver sits behind either Pam or Quiver
134.
135.
25) If Pam sits next to Neil and Kim sits next to Laine, then which of the
following must be TRUE?
136.
137.
138.
139.
140.
141.
A) Quiver sits behind Kim
B) Mary sits behind Laine
C) Quiver and Mary are in different jeeps.
D) Oliver and Mary are in different jeeps.
448
142.
144.
•
Answer Key and Test Taker Responses
143. Answer Keys
1. B
2. C
3. D
4. C
5. C
6. C
7. B
8. C
9. A
10. B
11. B
12. D
13. D
14. C
15. D
16. D
17. B
18. C
19. B
20. A
21. B
22. C
23. A
24. B
25 D
145.
146.
147.
449
148.
149.
150.
151. Test Takers Response Data with Answer Key as 1st Row
152.
153.
154.
155.
156.
157.
158.
159.
160.
161.
162.
163.
164.
165.
166.
167.
168.
169.
170.
171.
172.
173.
174.
175.
176.
177.
178.
179.
180.
181.
182.
183.
184.
185.
186.
187.
188.
189.
190.
191.
192.
193.
194.
1675-00000 BCDCCCBCABBDDCDDBCBABCABD
1675-10914
1675-10947
1675-10917
1675-10906
1675-10915
1675-10913
1675-10912
1675-10904
1675-10918
1675-10903
1675-10911
1675-10920
1675-10902
1675-10916
1675-10919
1675-10943
1675-10905
1675-10909
1675-10908
1675-10944
1675-10945
1675-10948
1675-10950
1675-10946
1675-10941
1675-10942
1675-10907
1675-10949
1675-10991
1675-10993
1675-10923
1675-10928
1675-10936
1675-10935
1675-10929
1675-10973
1675-10974
1675-10975
1675-10934
1675-10931
XDDCACBCDXCCXABAACXAXXXXX
BBCCCBBCBBBBCBBBBBBBBDDAD
BBDCBCBCAACAACDCBBCBCDCBB
BDDCCCDACBCDCCDDACABBDCEB
BCECCCEAABCDBBBABDABADDAD
BBDDDCXCXBCDCCXCCCCCDXBXD
CCCCCCBCCCCCCCCCCCCCBCCCC
BDDBDCBDABCCCCCBBBACDCABC
BDDCCCBCCDCDCCACBBBABBBBB
DCBCCCDCCBCDCCDAABABCDBCC
DCDCCXBAABCDDCBABCDXCXXXA
BCDCDCBCXBCDCCAXXXAXXCADD
BCDCCCDCCBDDCCBDXCBABCBCC
BCDCCCACABCDDCDBCCADBBBCA
CADCDCBCABBCDCAAXXAXXXXXX
BCDCCCBCABCDCCCXXXXXCABBA
BCDCCABCDBADDCDDXXCXCCAAD
BCCBDCDCCDCBDCCBCACBBCCDA
DABAACABCACBCCBBACBACBBCX
BCDBCCBCABCCDCCBBDABCADCC
BCDCBDBCCBCDDCCBBDABCDXAB
CCDCDCBCCCCCCCAABCCBBBBBB
BCDBCXBCABDDCCBBBCAACBCBC
BCDBCCBCCDCBDCBCDCCBBCXDD
BCDBABBEADCDCCXXXXXXCXXXX
CCCDCDBCABCDCCCBACCBACDCA
BCDCBCDCABBDDCDBDCAACBDCB
BCXBDCBCCXXADBXDXABACXAXB
BBDCCCBCABBBBDCCCCCCCDCBD
BCDCCCDCABBDCBACCCBABCCCC
BCDCCCBDABDDDCDDDAABBCCAA
CDDCCBCCDBCDDCXDACBACDBCD
CCDCDCBCCDBDDBBCCCBCCDCCC
BCDCCCBCABCDCCDDCAAABCAAA
CCDCCCDCCBCDCCDCCCCCCCDCC
CXCBXCBCCBBDDCAXXXXXDAXXX
BCECBCDCCABDCCDCABCBCBCBC
BBDDDCBCCBDDDCBCBBCBBCCBD
BCDACCDCCDCADDDDDDDDBDBAB
BDDCCCBCABCDDCCCACCCACDCB
450
195.
196.
197.
198.
199.
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240.
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243.
1675-10988
1675-10971
1675-10922
1675-10939
1675-10981
1675-10925
1675-10921
1675-10990
1675-10932
1675-10930
1675-10927
1675-10972
1675-10937
1675-10979
1675-10978
1675-10938
1675-10977
1675-10953
1675-10954
1675-10958
1675-10965
1675-10961
1675-10966
1675-10955
1675-10963
1675-10992
1675-10968
1675-10951
1675-10957
1675-10962
1675-10970
1675-10994
1675-10967
1675-10960
1675-10933
1675-10976
1675-10989
1675-10952
1675-10910
1675-10926
1675-10940
1675-20710
1675-20709
1675-20708
1675-20705
1675-20706
1675-20704
1675-20701
1675-20707
BXDCDCBCABBDDCDBXXXXXXXXX
CXDBDDDCDBCBDACBDCBDBDXCC
ACDCCCDBDBCDCCDBAACCBCABC
BCBCDCDCCBCDDCBCCCCCDCCCC
BDDDDCBCCBBECCCBCCAACCCCC
BCDCCCDCABCDDCCBCAACCBDBB
BCDCCXXXXDBBCCCXADAAADCXX
BCDXCCBBXBCDDCXCCCCCDDDDX
BCDCCCBCADBDCCCCCBABCDACC
BCDCCCCCCBCDDCCCCCCCCCCCC
BXDCCCXXXBCDDXBDXXXXDBDXX
BDDBCBBCXCBDCCBDACBXDCCBC
BCDCDCDCCBCDCCDBCDCBCBBBC
BCCBCCDCCDCDABADCCCCCCCCC
BXDCXCDBADCCDDBXBXADACBCC
BCDCCCDCCBBDCCDCCCCCDXXXB
BCDCDCBCABCDCCCCBCBDBDBCD
BCDCACDCABBDDCCCACCBCCCBD
BDDCBADDDBCACCDCCCCCDCCCC
CADBBCDCCDBACCCBCDBCBCACD
BCDCCADBABABDCABBBCBCCXXX
CDDCACDCDDCCCCBDAXAABXXXX
BCDCCCACBBDACBDBBCDCDDCBD
BCDCDCDCCADDDCDDCCCCCBBXB
CDDCCCCCCBCDDCCCCCCCACCCC
CDDBCCBCBBCCDCDCBAXABDCBC
BCDDCCBCABCDDCBAXCCBABCCC
BXBXXCBCXBCDDCDXXXXXBCCBD
CADBBCDCCDCACCADBABAAACBC
BCDCBCBECBBDCCBDCBBBCCBBD
CCDDDCBACBCBDCDAADBCCCAAA
BCDCBCDCABBDDBACCCBABCCCC
BXDDCCBCCDBDCBDBXXXXBCCBD
BCCBCBCCDBBDCCXBBCDXBAAAD
CCDCCCDCABDDDCACBDCABBACD
BCDCCCBDABDDDCCDACBABCBCB
BCDCDCDDDBBDDCCDDDDDBCABC
BBDDCCCDCDBCBDCCCCCCACDCC
CCBCCCBCABDDDCBDCCCBCDCBC
BCDCCCBCABDDDCDDXDBADAXXX
BCDCCCBCAACDDCCDBCABCCBDB
BCCDBCCCDDDCBCABDBBDBCBXA
CDDCCCBDBBBDBBCADDBBCBAAD
BBBBCCDCDBDBDCABBBBBXCDCC
BADBCBDBCBCDDCABBBDXDCADD
BCDBCCDCCABDDCCCECBDCACBD
BCDACCCCCBCDDCCBBBBBCAACB
CBDCCBADCBDDDCBDCABDBCBDA
BCXCXCDCCDBCDCCXXDBXCCXXC
451
244.
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1675-20702
1675-20820
1675-20818
1675-20817
1675-20807
1675-20808
1675-20814
1675-20802
1675-20801
1675-20803
1675-20804
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1675-20751
1675-20758
1675-20755
1675-20757
1675-20765
1675-20763
1675-20799
1675-20793
1675-20773
1675-20800
1675-20752
1675-20781
1675-20787
1675-20786
1675-20762
1675-20769
1675-20783
1675-20790
BCDDCCBCABBDCCBADDCBBDCAC
BADCDCDCABBDDCCCCCCCCDBCA
BCBCCCDCCBCBBACCBACBBCBCC
BCBCCCBCAAAAAAACCCCCBCADD
BCBCBCDABBDDCCCCBBCDCBBCB
CCDBBCBCADBDDCDCCCCCCCCCC
BCBCBCCCCCBDDCCCACACCCCDC
BCDCCCBCCBCDDCCDCCCCBCCBC
BCDCCCXCXBDDDCCXXXXXBXXXX
BCDCCCBCCBBDDCCCBBCCBCCBD
CDDCCCBCCBCDCCCCCCCCDCCAA
CDDCCCDCCCCCACCCCCCCBCCCC
CXDXXCXCAXXXDCXBCBBAXCDXD
BDDCCCDCCBCDDCDBCBCCCBDCB
BCCCCCBCCBCDBBABBCBBBCADB
BCDBBCBADBCDDCCDCDAACBCDA
BCDCCAAAABCDDCAAAAAABCACC
BDDCCCDCCBCDCCCCCCACCCCCC
BXDBXCCCCXXXXXXXXXXXBCABA
BXCXCXXEXAXXDCXBXXDXDCACD
BCDBCCBCACACABCACABADBBAC
BCDCDCBCDBCDCDCBCCACBBCBC
BBDCDCACBBDDCCDCBCDCCDCBC
BBDBCCBCCCCBDCBCBDADDDCBB
DDCBBCDCDBCDCCABDCDAAXBAC
BCDDCCDBCCBDCXACBCDCCBDCB
BDDCCCBCDBCDDCCACBBDADDBC
BXDBCCXCEACCDCXDXDEBDAADX
BCBCCCBCCBCDDCCBBBBBCCACC
BCDDBCDBDBBDDABCBDACBXXXX
BCCBACDCCCBBCCADBBDBCCBDA
BCBCCCDACBCCCBABDAAACDAAB
BCCBCABACABCCBBBDAXCBCBAC
CXDCDCBCAADDCBABCADAABDCB
BCCCECACABCDDACBACAACDBAC
BCDACCDCCBCDDCCCDCCBCDBAA
DDDCBCBCABBDDCBCCCCCXXXXX
CCDCDCBCABCDDCDCCBCBDCCBC
CCCCCCBCACBCDCCACCCCCBCCC
CACDDCDCCDBCDDABDBXADBCAD
CDCBACBCBCDADCBADADBCBDCA
CDBCACDCADBBCCCBDCAACAACA
CDDBCCDCDBCDDCBDBCCBBCCBB
BBDCCBDCABCADCBDBCDBDBCDA
CCDXDXXXXACXCCDBXXXXXDXXC
BDDBDCBCCCBDCDACAAAACABBB
BADAACBCAXCDDDXAAAAACDAXX
BCBXXDBCAACDCCDXXXXABXXXX
BCDCCCDCCBCDDCCCCBCCDCACD
452
293.
294.
295.
296.
297.
298.
299.
300.
301.
302.
303.
304.
305.
306.
307.
308.
309.
310.
311.
312.
313.
314.
315.
316.
317.
318.
319.
320.
321.
322.
323.
324.
325.
326.
327.
328.
329.
330.
331.
332.
333.
334.
335.
336.
337.
338.
339.
340.
341.
1675-20794
1675-20795
1675-20797
1675-20777
1675-20775
1675-20772
1675-20753
1675-20791
1675-20771
1675-20778
1675-20776
1675-20796
1675-20756
1675-20760
1675-20774
1675-20759
1675-20754
1675-20798
1675-20703
1675-20813
1675-20819
1675-20806
1675-20789
1675-18047
1675-10554
1675-10558
1675-10557
1675-10551
1675-10561
1675-10563
1675-10562
1675-10540
1675-10538
1675-10556
1675-10555
1675-10552
1675-10537
1675-10559
1675-10560
1675-10539
1675-10565
1675-10571
1675-10534
1675-10564
1675-10572
1675-10533
1675-10503
1675-10550
1675-10545
BBDDACBCCCCDCCBXXXXXADCCX
ADBXXCBCAABCDCACXCABCACXX
BCDDDCBCABCDDCBCCCBACCACD
BCDCCCDADABCBACAABDBACBEB
CCBBACBCADDDBCACXXXXXXXXX
CCCBDCBCADBADCADCBAACDBCC
BDDCCAACABCDDCAAAAAAAAAAA
BBDDCCCCCDBCDXCBCDCBCCCCC
BCCADCDCCBBBDCAXXCXAXXCAB
BCDCCAACBAACDCBCXDCBABDCC
CDDBACBBCBCBCCABXCBXCXDCC
BCDCDCBCACDDCCCXXXXXBCXXX
BCDCXCBCCBDDDACBBCDBCBCDA
BBDCBCDCCBCCDCBBCCCCBBCBB
BBDCXCBCABBCDBACBCBCBCCBX
BCDCCCBCABBCCCABCDABBCACD
BBCCACBCABCCBDABBBCABBBCA
CXDCBCDCCDCDDCDCCCCCDDDDD
BCDCCBBCABDDDCDCCBBCACAAC
BCBCCCBCCBBDCCCCBCBXCCBCB
BDDBCCBCABDDDCDCBCBDBCACD
BCDCCCBDACCDDCDDBBAACAADB
BCDCCCBCADBCDCBCBDCBBCACD
BDCBXBDBCDABDCBCDXDCBBACA
BCDXXCBCABXXCCXBDAXBAXAAC
BDDCCCBDABDCDCCDACDABCDBD
BCBXACDCDBCXCCBBAAAACBDAC
BBDDBCDDBBCDDCDCDDBBCCABA
BBCDDCDACBCDCCCDABABCCBCD
BCDCDCDCCBCDCCDCCBCCBXABA
BCDCCCDCABBDDCCBCDBACCDCB
BCDDABDCACDCACBCDACCDCABB
BCDCDADCDDCCDCBCDBACDBCCB
BCDCBCBCCBCDACCCBDCAACAAC
DCDCXCBCBBCACCCDCBDADBCAA
BCDCDCDCDBBDDCDDACBAXAAAA
BDDCCCBCABBDCCCDXCBACBCBA
BCDBCCDCCBCDCCCBDCBABCDCB
BADCXCBCCABCCABBXXAAXXXXA
BBACDCBCABCDBCACBCCCCCCCC
BDDBXCDBABCDCCBBBCCCCBBCC
DDDCCCCDABDDDDBCBBBDDDDDD
BCCCBCDBBBBDCCBDBABCDCADB
BADCCCBCCCDADCCDCBBDBBBBB
CBDDBCDCCDBDDDCCCCBBDABCD
CCDXCCBAABCCDCCCACDBBAACB
BCDDDACBCABDDCDBCDDBCDBCD
BCCCCCBCABDDCCCCCDCCCDDCC
BCBDCCBCABCCDCBCCDXXXXXXX
453
342.
343.
344.
345.
346.
347.
348.
349.
350.
351.
352.
353.
354.
355.
356.
357.
358.
359.
360.
361.
362.
363.
364.
365.
366.
367.
368.
369.
370.
371.
372.
373.
374.
375.
376.
377.
378.
379.
380.
381.
382.
383.
384.
385.
386.
387.
388.
389.
390.
1675-10505
1675-10547
1675-10526
1675-10546
1675-10527
1675-10528
1675-10531
1675-10529
1675-10549
1675-10532
1675-10548
1675-10501
1675-10502
1675-10543
1675-10517
1675-10504
1675-10506
1675-10512
1675-10542
1675-10507
1675-10541
1675-10522
1675-10510
1675-10524
1675-10523
1675-10525
1675-10509
1675-10508
1675-10519
1675-10514
1675-10530
1675-10511
1675-10513
1675-10516
1675-10521
1675-10544
1675-10535
1675-10553
1675-10520
1675-10515
1675-20283
1675-20282
1675-20281
1675-20263
1675-20262
1675-20260
1675-20259
1675-20261
1675-20269
BCDCCBCBABDDDACBABCBCCACD
BDDCCBBBBBDDCCDAAAAAACAAA
BCCDBCDACBECDAEDBDCACADCA
BDCBCCDAABCDCAADBCABCDABB
BBBBCCDCDDCBADCABCADBCCCC
CBDDDCBCABBADCCDBDCBACBDA
BCDCBCDCCBCBDCDBCBDBCCADA
BDDCCCBCDBCDDCCCCCBACCCCC
BCDCCCBCABBDDCBBCDBABCXBD
BCDCDCBCABCDDCACCCCCCDBCB
BCDCCCDCBACCDEDACCBADCABB
BCDABCDCCBDDCDBDABCBDCACB
BCDXXCBCABCDDCBXXXXXXXXXX
BDCBACBADBCDDCCDACBACADCD
CBDCCCBCCBDXDCCADCAABCAAA
BCBCCCBCABBDDCDBCDBXBXXXX
BCDCCCAACDDDDBACCCCCBDAAD
DBDCACBCCBCDDCCBCCDDCDCDD
BBBCCCBACDBDBBBDBAADBCBCB
BCDCACDBCACXCADDCBXCBDAXX
BCDCBCDCABCADCDCCBCBDACCC
CCDACCBCCBDDDCCCCCCCDDDDD
BBDCBCBABBCDDCCBBBBBABBBB
DBDACABCCBCDDBACBDBAADBCC
CBDDBCBCAADCDCBBDAACCDDCX
BBDCXCCBCBCADCBCDBACCBCAC
CBCBACBCEBCDDCABDXBBDBBDA
BCDCDCBBBBDDDCDBBBBBBDBCD
BCDDCCDACBCDCCBBBCACCCBBB
BCBADCBCABDDCCDDDCBACCABX
BCDCBCBCABBDDCDBCBCBBDBAC
BCDCBCBCABCDDCBBBBBBBAABB
BDDCXCDCCBCDDACXXXXXXXXXX
BCDCCCBCABDDDCDDCBBABCABD
BCDCCCBCABBDCCCBACACABDCA
BDDCCCDCXDCBDCCBCAAABCACA
BCDCCCBCCBDDDCCBCBBCBCBCD
BBDBBCBCABDDDCADACBABBBBB
BCDCDCBCCBDDDCCDACBABCAAD
BCDCCCBCABDDDCDBBBBBBCABB
BCDCCCBCADBCBBABCBDBCCBDA
XXCXDCDCABCACADBDACBBCABC
BCCCBCBCABCDDCXDDCAXXXXDC
BCCADCBCACDDCDACBCCBCCDCC
CDCBCCBCACBBCDCCBCCDDBCDC
CDDCCCBCABDBCBCBCACDCBBCD
BXDCXCBCACBDDCCXXCBABBDBX
BDDBBDBCBBCDDBDBCADCAADDD
BDDCCCBCADCBDBACBAAACAACC
454
391.
392.
393.
394.
395.
396.
397.
398.
399.
400.
401.
402.
403.
404.
405.
406.
407.
408.
409.
410.
411.
412.
413.
414.
415.
416.
417.
418.
419.
420.
421.
422.
423.
424.
425.
426.
427.
428.
429.
430.
431.
432.
433.
434.
435.
436.
437.
438.
439.
1675-20257
1675-20266
1675-20270
1675-20267
1675-20251
1675-20252
1675-20253
1675-20256
1675-20255
1675-20254
1675-20268
1675-20258
1675-20284
1675-20285
1675-20639
1675-20640
1675-20638
1675-20637
1675-20696
1675-20699
1675-20264
1675-20382
1675-20698
1675-20700
1675-20265
1675-20380
1675-20379
1675-20378
1675-20377
1675-20381
1675-20400
1675-20399
1675-20398
1675-20397
1675-20396
1675-20395
1675-20394
1675-20393
1675-20392
1675-20391
1675-20695
1675-20312
1675-20324
1675-20322
1675-20321
1675-20323
1675-20325
1675-20305
1675-20315
BCBCBBBBCCCCDCCBBBBBBCAAC
BCDCXCBCABCDCCXADBCBCACDB
BCBCCCDCABCDDCBABCBBACBBC
BCDCBCBCADCBCCDBCACBCBBDB
BCDDACBCBDCDCCDCABBAACAAC
BDDCCCBCAACCACBDBCBCDACBC
BXDCCCCXXCBDCCXXXXXXXACCD
BXDCBACXABBXACBDBCABCDDXC
BXDCCCBACCCDCABXXXXXACBDB
ACDBDCBBABBADCADXCBBDBDCB
CDCBACBCBBBACCDACBDCAAXAB
BCBCCCDADBCDDCDDBXABADCDA
BADBACDCCCBBCCBACBABBCBCA
BBDBDCBCCBACACCBDACBBACDA
BACDDCBDACDBACCABCCDBCBCD
BABCDCBCABCCDCDBXBXCACADB
CDBCCBDABCCBCCBDCBBDCDDCB
CCDCCCDCCBBDCCBCABCABBCDB
CDDCBCDCCDBCCCDCDCBCDBCDC
BDDCCCBCABCDDCADBBCAADACD
BCBCDCDCCBDCDADDCDCCDDCCB
BDDCCCBCABBDDCDCDBCDCCDCD
BCDCCCBCABCBDCBABCCDCDBDC
CCEBCCBCADCDDCBBDCDBCCADB
BBDCCCBCAABDCCDBCAAABCCCC
BDDCBCBCABCCCDABCDCABCBBC
CCBDBCBCABCDACBACDACCBDBA
BCDBXCBCCDBCDCBXXXXXCBDAC
BBCCDDBEDCBDBCABCDCBABDCA
DCBADCBACACCACDBDADACCDCC
CDCDCDADBACBBDBDBCABCBACA
BCDCBCBCABCDDCDCDBABCADBC
BBBCDCDCCDCDCCABCDABADDAC
BCDCCCDCCCDCCCACDCCACCDCB
BCCBDCDCCCCBDCDABBABAACCA
CCCBXCBCCCACCCBDBBACCDXAC
BDCBDCBCABACACBDCBBDCABDC
BCDCCCDCCBBCCCADBDDDACDCD
CCDADCACBBBDDCXACCBBAACBD
BCDACCBAABCBCCBCDCBABACDC
BCBBCCBCACBDBCBDCBABCBDBC
CCDBCCDCCACBBCACDCBDCBDBD
BCBCABBBBDABDCABBCAABCCCC
BCDCCCBCADCCDCBBCBXDBCXXC
CCCCCCBCABCDBDCXXXXXAACCB
BDDBCCBCCACDDCADDCADACCBC
CDDDDCBCABCADCDBACDBACCBD
CCBCDCBCADCDCCACDCBDADBDC
BDDDBCDCCDCDCCAABCBCAABBA
455
440.
441.
442.
443.
444.
445.
446.
447.
448.
449.
450.
451.
452.
453.
454.
455.
456.
457.
458.
459.
460.
461.
462.
463.
464.
465.
466.
467.
468.
469.
470.
471.
472.
473.
474.
475.
476.
477.
478.
479.
480.
481.
482.
483.
484.
485.
486.
487.
488.
1675-20311
1675-20308
1675-20250
1675-20231
1675-20232
1675-20234
1675-20233
1675-20227
1675-20236
1675-20248
1675-20228
1675-20240
1675-20229
1675-20239
1675-20238
1675-20235
1675-20237
1675-20245
1675-20242
1675-20243
1675-20244
1675-20247
1675-20249
1675-20246
1675-20273
1675-20280
1675-20687
1675-20693
1675-20692
1675-20691
1675-20690
1675-20689
1675-20688
1675-20686
1675-20279
1675-20278
1675-20276
1675-20277
1675-20275
1675-20274
1675-20272
1675-20271
1675-20694
1675-20610
1675-20287
1675-20286
1675-20288
1675-20605
1675-20607
BBCCBCDCCBDCDCABCDBACBDAC
CBDCBCBCABBDDCBCABDBACABC
BCBCDCBCCDCDCCCCDCCCBDCCD
CCDABCDCABCDCCCBCCCCACCCC
BCBDACDCXBCDBCBDDCBBAACBD
CCDBADDCBCDBCCCADCBCBCBCA
BDDBCCBCACBDADCCADBAABDAD
CDCBCCDCDBCACADCCCBBBBAAA
BDDCDCDCADCDCCADCBDADXXXX
BCDDCCDACBBADCCCABBADBABC
BCBDCCBCBCBCCCACBCAAACBBA
BDDCDCDBABCACCACDCBCBDCCB
CBDCCDBCCBCDDAABCCAABCDBC
CDDCDCBCDBCDDBCBACACADBBC
CDBCDCDCCDCDCCCACCAACCDCD
BCCBDCCBABCDCCACBCBACCDBC
BEACDCBCDDBDACACXCDACXXXX
BXEBXCXBDACDACXXXXXAXXXXX
CDCCCCDCCCCDDDCCBCCCBCCDC
BCCCXCBCABCDCCCDDCABDDACD
CDDABCBCCACBADCBDAAAADCBB
BBDACCBBDBCDCCDDBDBCADACA
BCCDACBEABDADCADBCAACBXXX
BCCCDCAAABBBDCACBDAACCADD
BCDCCCDCCBBDDCBCDBCDCCADC
CCDDCCECCCCBBCBCBCCCBBBCC
BXDCCCDAXDBBDCCCCXCCCCCCC
CXDXDXXXXBCDCCXXXXXAXXXXX
CXDDBCBCXACBDCBXXXXAXXXXX
BXBXBCBDCDCBADCAXCXXXXXXX
BCBCCCDBCCCACCBBDBAAAADAC
BCDACCBCABCBDCBBCDBACCEBC
BCDCCCBCABCCCCXXXXXDCBXAC
BCCXXCBCACCDCCAXXXXXXXXXX
CBCDBCDCCBDCDAAABCBADBCDA
BDCCDCBXXBCBBCXXADBAXXXXX
BCDCCCBCABBDBBCBBBBBBCABD
BCBCDCBCCBBDDCCBBCAACCBCC
BCBCCCBCABCBECCDBBCBCBDCB
CDDBDCACABCADCCAXCBCBCADX
BDDBCCDBDBBABCCDACBCBDXXX
BCDCDBACADCCBCCCDBCAADBAC
BCCDCCDCCACDDACBBCDABBCBA
BCBCCCDCABCADCACCDBCDCDCB
BCDCDCBCABDBCCBDBCDDACDCB
BADCCCDCADCBCCDCDACABCBBD
CDDCCCBCACDACCADBCABBACAD
BDCDCCDCDBCBDDACDBCCACDBC
BCCCCCBCABBDDAABCBBCBBCCC
456
489.
490.
491.
492.
493.
494.
495.
496.
497.
498.
499.
500.
501.
502.
503.
504.
505.
506.
507.
508.
509.
510.
511.
512.
513.
514.
515.
516.
517.
518.
519.
520.
521.
522.
523.
524.
525.
526.
527.
528.
529.
530.
531.
532.
533.
534.
535.
536.
537.
1675-20604
1675-20602
1675-20603
1675-20606
1675-20608
1675-20609
1675-20682
1675-20683
1675-20684
1675-20685
1675-20661
1675-20663
1675-20664
1675-20665
1675-20666
1675-20667
1675-20681
1675-20668
1675-20669
1675-20670
1675-20671
1675-20672
1675-20673
1675-20674
1675-20675
1675-20676
1675-20677
1675-20678
1675-20679
1675-20680
1675-20220
1675-20221
1675-20208
1675-20219
1675-20217
1675-20218
1675-20212
1675-20213
1675-20216
1675-20211
1675-20214
1675-20215
1675-20225
1675-20224
1675-20202
1675-20203
1675-20204
1675-20206
1675-20207
CDDBDCBCCBBCCCACBDCBCABCD
BCCCDCBCACCADCADBCACDABCC
BCCAECBCADBDDCDBACBBCABDC
BCCCADBCABCDDCBBCCBAABCBB
BCDCACDCCBBDCCDBADCBCCAAC
BCADCBCADBBDDCBCABDADCDBD
BDDCCCBCAACDDCCXXXXXBCBXX
BCDDDCBCABCBCCBCCCXXDBADC
CDDCACDADBBCCCBXXXXXDDACD
CDCDBBCDCBCDDBABCDACBCDCD
BCCCCCDCCBCDDCABCCADAACBC
BACBACAACDCADCBDABDAADCAD
BCADCCBCDBCDDCAAABCBACCDC
BDCDCCBCABBDDCABCDACCCABC
BDCCXCBCDBCAACBCBCBCDCBCC
BBBBDCBCCCCDCCCBXXXXCXXXX
BBDCXDXXXBCDXCACXXBDXDXBD
BBDCCCBCABCDDCCBBBBBCDCCC
CDBACCDCCCBCDCDXABBABDDCB
CCBCCCDCCDCDDCBBDBAACDDBC
CDDCCCDAADCCDCAAACBDBCAXX
DDDBBCDDCBCBBCDDBCABBCDBA
BDXXXCACADCDDCAACDBCAXXXX
BCDCCCDCCBCDDCEBCDCCBCBCA
BCDCDCBDABBDDCCABCABAADAD
BDDCDCDCACBBACAAABCABDCCD
BDDCDCDCCBBDCCCCBCCDCCCCC
BDDCDCDADDCACCDDBABDDDBCD
BCDCBCDCDBCDDBACADCBCBDCA
CBBCCCDCCBCDDCCDBBAABDDBC
BDCCDCDAADCACCBDADAABCCDC
BDCCCBDCBCCECBCCBABBCBDCA
BDCCCCBCABCBCCCDACBADXXXX
BDDCBCBCCBBDDCCBCAACACBCC
BBDDCCDCBBCCBCDCBCBCBCBCB
BCDCCCDCAXXXXXXXXXXXXXXXX
BDCCDCDCCDCABCCCDBCACCABD
CDDCDCDCCDCBCDDBCXBABCADD
CDCDCCBCCDBBACACDBACCCBCD
BCDBDCDCCCBBDAADBACBADCDC
CDCBDCBDCABCACDCBDAACCDBD
BDCECCBCAACDDDBCBABCBDCAB
BBCBDCBCABCCDCADACAABADAC
CBABBCDCBAABCACBCDCBCCBCA
BCCBABBDAACCDCBCABACCDCDD
BCCBCCAAABCDBCBCDDADABCCC
ACDDDCBCABCAACADCCBACXBCD
CDDBCDDCCBCCBCBDBDCCDDCDC
BDDCCCCCAECBCDCDCCDBCACBD
457
538.
539.
540.
541.
542.
543.
544.
545.
546.
547.
548.
549.
550.
551.
552.
553.
554.
555.
556.
557.
558.
559.
560.
561.
562.
563.
564.
565.
566.
567.
568.
569.
570.
571.
572.
573.
574.
575.
576.
577.
578.
579.
580.
581.
582.
583.
584.
585.
586.
1675-20210
1675-20205
1675-20201
1675-20222
1675-20209
1675-20329
1675-20327
1675-20339
1675-20371
1675-20352
1675-20353
1675-20355
1675-20356
1675-20354
1675-20358
1675-20351
1675-20357
1675-20360
1675-20359
1675-20364
1675-20369
1675-20370
1675-20363
1675-20367
1675-20365
1675-20366
1675-20372
1675-20373
1675-20374
1675-20375
1675-20368
1675-20362
1675-20361
1675-20306
1675-20318
1675-20304
1675-20319
1675-20309
1675-20301
1675-20302
1675-20303
1675-20320
1675-20317
1675-20307
1675-20310
1675-20314
1675-20316
1675-20313
1675-20660
DBDBCCDCCBCDDCDBCCAACCBBC
BDDCCCBCADCCDCBBBCBCBCDAB
BCDCBBCBBCBCCCDDBCDBCBCAA
CDDBCCBCADCDXCACBBACABBDC
CDDBDCBCABBBADCBBBBBABABA
CDCDDCDAABCDACBAACDABADCB
BADBECDCABDABBBBXXXXCDXAX
BCDABCBCCBCBDCCCCCCAABCDC
CDDCECBCAABDCCABCDACBBACD
CCDBCCDCCBCDDCABDCBCACDCB
BBDCXCDCCDCDDCBCBCCCCACCB
CBBCCCBCABCDCCBACDBBCBCDA
BBBCCCDACBDCAABBCDBAABCXC
BDDBBCDCCCCAACBCCDAABABCA
BCBDADDBCBCDDCBDCAAACDCAD
CDDDCCBCCBCBDCDDDBBCCDBBB
CADBCCBEAABBCCCBCBCBCCABD
CBBDCCBCAACDCCCDDCBACABDC
BCBDACBCADCDCCABDBADCCAAD
BBACCCBCABCDDCBXXXXXCCCCC
BDDCCCBCDBCDCCDDBCBAACDCB
BCCCDCBCDDCDDCAABBCCCDBAD
BDCCBCDCCABACCBDDBAAABCBD
BBCBBCBCCABCCCBCBCBBBBBBB
ADCCCBDCDCBBACBBCDBCABCDB
CCDBCCBEABBBAAABAABABAAAA
BDCBCCDCCDBBDBCDBCBDBDBCD
CBBDABDCADDCDCDBADCACBABD
BCCCDBDCCCCBCAAADAACACAAB
BDDCBCBCCCCBBCCCCCCCCCCCC
BDDABCDCCBCDDCABCCBAABCBC
BDBCCCBCCBCDDCBCCCCACCCCC
CCDCCCXBBCBADCBDACBACXXXX
CABCDCDCCBACDBCABDCCDABCD
BDDCBCBCDBBDDCCDACBDBCDAA
BDBCXCBCCDCDCCCDXXXAXXXXX
BDDDBCDAABCDCCDBCABACCABA
BDBCBCDCCCBAABBCABAAABDAB
CCCCCCBCABCADCCDCCACBBBBB
BCBBBBDCBACBDBAABAABBBCBB
BADBXCDCCCBDDBCBDCCCABCCB
DBDBCCBCADBAACADCBDACXABD
BBDCDCBCCBCDDCBABBBCCDACC
CBBACDABCDDACCBDBCDADACCD
BCBCCCBCBBCCABABCDBCACCCB
BBDCDCBCCBCACBABCDACAADBC
BCDACBDCDBCDDBCBDCDCADBCD
CDCCDCBCCABXDXDDCCADBCABB
BCDCDCDABBBCDCBCBDABBACBA
458
587.
588.
589.
590.
591.
592.
593.
594.
595.
596.
597.
598.
599.
600.
601.
602.
603.
604.
605.
606.
607.
608.
609.
610.
611.
612.
613.
614.
615.
616.
617.
618.
619.
620.
621.
622.
623.
624.
625.
626.
627.
628.
629.
630.
631.
632.
633.
634.
635.
1675-20631
1675-20632
1675-20634
1675-20633
1675-20635
1675-20641
1675-20643
1675-20644
1675-20646
1675-20648
1675-20655
1675-20654
1675-20647
1675-20656
1675-20657
1675-20658
1675-20651
1675-20642
1675-20652
1675-20645
1675-20653
1675-20659
1675-20649
1675-20337
1675-20336
1675-20335
1675-20334
1675-20333
1675-20341
1675-20343
1675-20332
1675-20331
1675-20349
1675-20350
1675-20342
1675-20344
1675-20345
1675-20346
1675-20347
1675-20340
1675-20348
1675-20338
1675-20326
1675-20328
1675-20330
1675-20622
1675-20293
1675-20619
1675-20611
BDBDDCDCADCCBCCBDAAABCBCB
BDDCACBCACCBDCDABBBCBCDAB
BCDCCCBCACBAACBCACBAACDCC
BDCBDCDACCCDDACBCABCABBCD
BCCCCCBADABDDABCCCCCBAAAA
BADCDCDCABCDBCABCBCBCDBCB
CDBCCCDDCDCDDDBCCCCCACDAC
CBACDDDCADCDDAAACBBCADCBA
BCDACBCBCBCDCCCACCBCBCDBD
CDBCBCBCABCDCBABCCCCBCDAD
BXCDBCDCCBBAACBCDCABBACCB
BBCCCCBCADCDCCACBDBAACBDC
BBCDDCBCCBCDCCAADBABAABAA
BBCBBCBCCBBDDCACCADBCCADB
BBDCCCBCADBBCCDBDBBCCADCA
CDDCDCBCABAABCADAAABCDCAC
BDCBCCBCABCACCDCDCADACADC
BABCDCDCABCBDCABCBDABDCCA
CBDCBCDBCBCDDCACABABCBABB
BCBBDADCACCBDBDDACBADCACD
BCBCCCBCABCDBXCCDBCDBAABD
DDDCBCBCABCDCABCBCBCCCCBD
CDCCACBCBBABCCDCBCACAABCC
BDCCCDACAADBCCCDBCBDBDBDA
BXBCCCXXXBCDCBDXXXXXBCAXD
BDDCCCDCABCDBCABCDABADBCB
BXDBCCBCACBXXCBDACCAXCBXA
BCBCCCBCABCDCCDBCBCCBCABC
CDCBDCDCCBCADCBABCBACCACB
CDBBDCDCDBCBDCBDBCABCBDCC
BXDCDCDCADCCCDDCBCXXBCADB
CCBBCCBCDBCCDCCABADCABDCB
CCDACCDCABCCCAXXXDCXCXXCX
DBCBCCDCACBCCACCDCABCDCBA
CCCCCCDCCBBCCCCBBBDDDDDBD
BCDCDCBCACCDDCDBACBABCADA
BCBCDCBCCBBACCXXXXXXAXADB
CABBCCBCCAACACABCCBBACCXX
BCBCCCBCCBBCCCCDABAACBCDA
CDDBCCBDABCDDCBCCAABCCBDC
BDDCECBCCADBCCADBCADCADCB
BCDCDCBDCBCBDCCAAAAADBXDC
BCCABCDCDDCDADCBBCACBDBCD
CBDCDCBCCBDBCCADBCDACBDCB
BDCCCCBCDCCDCACCCCACABCCC
BCDCCCBCCDACBDBABCBAABDAB
DDDAXCDCABCCCCDBDADAXXXXX
BCDCACDCBBADCACABDABCBDCA
BDCBCCBCAABDCCABDBBBCBDDC
459
636.
637.
638.
639.
640.
641.
642.
643.
644.
645.
646.
647.
648.
649.
650.
651.
652.
653.
654.
655.
656.
657.
658.
659.
660.
661.
662.
663.
664.
665.
666.
667.
668.
669.
670.
671.
672.
673.
674.
675.
676.
677.
678.
679.
680.
681.
682.
683.
684.
1675-20614
1675-20629
1675-20612
1675-20628
1675-20615
1675-20613
1675-20620
1675-20291
1675-20623
1675-20626
1675-20627
1675-20625
1675-20624
1675-20292
1675-20616
1675-20617
1675-20630
1675-20618
1675-20294
1675-20223
1675-20376
1675-20697
1675-20662
1675-20241
1675-20226
1675-20636
1675-18732
1675-18735
1675-18724
1675-18740
1675-18736
1675-18741
1675-18742
1675-18731
1675-18730
1675-18734
1675-18728
1675-18722
1675-18721
1675-18726
1675-18309
1675-18310
1675-18737
1675-18729
1675-18723
1675-18750
1675-18738
1675-18739
1675-18725
BCECBCDABCBCDCABDCACDCACD
CCDBCCBDABCDBCAXAAAACBCXX
CBDCACACCBBADCDDABCBBCBCA
BCBCCCBCADCDDCACXCAABCBCD
BCBDDCCCAXCDDCXBBXAXCXXXD
CDDCCCDCCBCDCCBDCDBCCDBBA
BCBDACBCABCABCABCAADCDACC
CCBBBCBCABBCDCDCACBACDADC
BCDCCCBCCBDDDCCAABBCAABDB
CDDCACBCABCCDCBBBBBBBCAAA
CDDCCCBCCCBDDCCDBCAACBCAA
BCDCCCDAABBDDCADDCBCACBBA
BCBCDCDCCCBDDBCBDCBCBBAAD
BCBCDDECCCCDCCABCBCBEDBCC
BCDCCCDCCBCABCADBCBAABABC
BCBCDCBCDBBBDCCACBBDBDBCA
CDCBDCDBCBBACDBBCBBADCACB
BCBCCCBCCBCCDCCBDCAACABCD
BBBDBCDCCBCBDCBDBCCDBDXXX
BBBCCBBCABCADABAACCABBAAA
CDDBCCBCDBCDDCBCDBAAADDDB
BCCBDCDCCDCADCACABCCDABAC
BACCDCBCABCCCDBDCDABACBDB
BCDCCCBCACCDDCBDBDCCBCABD
BXDCCCBCACBDDCBDCCCCCDCCC
BCDCBCDCABBDCDCBACBDACABC
BCDCDCDCCBCDCCDDDCBACBBBB
BDBCBCBAABBCDCABABAABCCCA
CDDDACDCABDDDCDDACBAADCAC
BADCBCEDDBDDDCDCDBCAAAAAD
BDDCCCBCABDBBCBCCCCCDDDDD
BCDCCCDACACDCCCBXACACBABD
BDDCDCBCABCACCBCDDAADBCBD
CCDCDCACABCDCCCDCBCDCDCBD
BXCXXCBCAXBXBBCXXXXXXXXXX
BBDBCCBCABCDDBBCBABABBCCA
BDDCBCCCCDBCDCEDBDAACACBD
BCDBXCBCABCDDBABCBDCCBCDC
BDDCBCBCCACEDAACBECABACDB
BDDCDCBCCABDADCDCBDBCCBCD
CCBBCCDCCBDDCBBBBBABCDBBA
BCDCCCBCCDCADABCBACADCADB
BDDCBCDCABBDDCACBDAADBBDA
BCDCCCDCABCDCCCDACCBBCABC
CDCACCDCAABDDAACCCCCDDDDD
CBDCCCDCCBCBDCABABCBAADCB
BDDDCCCDADCCDCACCCACBCCCC
BBCDBCDCCBCBACABBBBBCCCCA
BCADACBBADCDDADDCAABCBCDA
460
685.
686.
687.
688.
689.
690.
691.
692.
693.
694.
695.
696.
697.
698.
699.
700.
701.
702.
703.
704.
705.
706.
707.
708.
709.
710.
711.
712.
713.
714.
715.
716.
717.
718.
719.
720.
721.
722.
723.
724.
725.
726.
727.
728.
729.
730.
731.
732.
733.
1675-18749
1675-18744
1675-18745
1675-18746
1675-18747
1675-18748
1675-18101
1675-18743
1675-18727
1675-18771
1675-18776
1675-18774
1675-18777
1675-18775
1675-18778
1675-18765
1675-18764
1675-18444
1675-18456
1675-18376
1675-18464
1675-18452
1675-18453
1675-18457
1675-18460
1675-18617
1675-18462
1675-18450
1675-18449
1675-18442
1675-18441
1675-18451
1675-18459
1675-18374
1675-18614
1675-18615
1675-18446
1675-18445
1675-18618
1675-18448
1675-18443
1675-18375
1675-18619
1675-18616
1675-18447
1675-18455
1675-18463
1675-18454
1675-18620
DDCBDABCDCDBADACCBADBCBCD
BBDCCCBCBDBBADBCBCBCXXXXX
BCDCDCBCCBCDDCBBDADBDXCAX
CCDCDBDCCBCDCCAAAAAACCCCC
BDDCBCBCACBABCBABCDCBDBDC
CCBBCCDCDBDDCCCDDBBCCBCCX
BCDCBCBCABCDCCBBCBDBCDCBB
BDDXDXXCDBCDBBDCBXXCCCDXX
BCCCCCBCCBCCDCDCCBCDBCCCA
CDCADBDCCBADDCBADBAADACBA
BCDCCCBCABCDCCDDABDCBBDAC
BEDCCCBCABDDDCDCBCBCXXXXX
CBCCCCDAABBBCCBBCCDDDAAAA
CCDCCDBDCBCDADDABCABCBDCB
BDDBACBCBDCDDCBBBBBBDBCCC
BCDCCCBDACCDDCCCDCBDCBDCC
DBBBBBBBBDBBACDBBBBBABBBB
CBBCDDCDBADACCCCBABBAAAAA
BCDCDCDCCCCADCXAABBCABCBA
CBBCDBDACAACDCBCDBCBADCBC
CCCABBDBCAACDABCDBDBAAABA
ADBCCBDBCCCADCCADBBDCAAAA
ADCBABDBACACDCCABCCCCCCCC
ACCBDBDCCAAACABACCBCCBCBA
ABCBCBABCABCDBBADABADDBBD
BCCCCBDBCBACCABCCADCBBBBB
CBDACBDBCDCBADCBCADCDABCA
AACBDADBDAACDCBBDBADAACBA
ABACCADBCCABDBDCACACBADCB
ABBBBBDBCCACDABCCADCCDADA
AABDCDCADDCADDBCBCCBABACA
BCBCBBDBCADADCBCCACABDCBA
CCCCCCCCCAACDABBCADCBBCDA
BBBBBBDBCDACDCDDCBBAAABBA
BCCABBDCCBADDABDDCABAACBA
BCCACBDBCDBADCBCCXDCBACBA
ABAACBABCCABDCCEBCBEBBABE
ABCBBCCBCDDCADBBCCBCABCDA
ABCCBBDDCBCCBCDAEACCCABDB
CDDCADDABDCABBDCACACBBACD
ACBDXDDXXDDDDAXCDBCDBBACA
ACCDEBDBCADABBBABDXCBXBCC
CBCCBBDBCABBCBCDABBACDCBB
BCADBBDBCDCACBBXDAACBCBDB
BCDBABDBCDAADCAABBAABBCCA
AAADBBDBCDCCDXXCCXDCCBACX
CACBBBDBCBDCADBBCBBDABBCD
BCACCBDBCDAACCDBBCDACCCCC
AAADBBDBCDCABXXXXXXXDDADA
461
734.
735.
736.
737.
738.
739.
740.
741.
742.
743.
744.
745.
746.
747.
748.
749.
750.
751.
752.
753.
754.
755.
756.
757.
758.
759.
760.
761.
762.
763.
764.
765.
766.
767.
768.
769.
770.
771.
772.
773.
774.
775.
776.
777.
778.
779.
780.
781.
782.
1675-18871
1675-18911
1675-18872
1675-18799
1675-18798
1675-18791
1675-18874
1675-18796
1675-18873
1675-18885
1675-18889
1675-18888
1675-18887
1675-18881
1675-18793
1675-18797
1675-18882
1675-18883
1675-18800
1675-18794
1675-18886
1675-18879
1675-18913
1675-18877
1675-18878
1675-18875
1675-18792
1675-18876
1675-18795
1675-18912
1675-18884
1675-18856
1675-18927
1675-18855
1675-18928
1675-18929
1675-18854
1675-18853
1675-18852
1675-18850
1675-18867
1675-18868
1675-18066
1675-18145
1675-18080
1675-18081
1675-18070
1675-18077
1675-18073
BDDCCCBCADCBCCDCABCCDBCCB
CXCACCBCABDDCCXXXXXXXXXXX
BDDACCDCBBADCCDCBADBCADBD
CCDACCACCACCACCCCCCCCCCCC
CCCDDCBCABCDDBBABBCBDCBAB
CCDBCCDCCBBDCCCABCABBCACC
CACBACDCABABDDACBCACBCBCB
BDDCCCDCCBCDDCABCCBCCBCCA
CBDCCCDCCBCDDCCADCBACBBAB
BCDCACBCABCDCADCBAXXXXABX
BDCCBCDCEADCDACBBBBCCCCXX
CCDCECBDCBDDCCDCBCBACDBCB
BBCXACBBXACDACBCDXBDDABCD
BDDCCCXCCCCDDCDCCCCBBDABD
BDCBCCCCDBCACCDCCCCCBDABD
BCDCBBBCADDCCDCDBCBACDBCB
CCDXXCDBCDXXDCXDXAAAXXACC
BCDCCCBCCBCBDCCCCCCACCCCC
BDCBCCDADCCAACCBBCCCABBBB
BDCCDCCCDDCCCCCBDCCCACADA
BCDDXCBCABBCDCBXXXXXXXXXX
BDDXDDDABBCDCCXDDABABABAB
BDBCCBBBCBCDDBCDCCBAACBDC
BBDCBABDDCDAACBABCCCBBBBA
BCBCCCBCACBCDBCABCCBDACCB
AAAAAAAAABCCDCAAAAAACCABA
BXXDCCXCBDCACDBDBCABXXXXC
BCDCDBCCDBDDCCDCCCCXXXXXX
BXAADCBDEBXXDBCCCXXXACXXX
BCDDCCBCABBBDCACACABADCDC
BXCCDCDCXBBDDDBAAABXABBDX
BBDBBXDCCDDDDCDDCABABCCBX
DDCAXBDXACDDAXXXXXXXXXXXX
BCDCCCBCDBCCCCACBBABBCBDC
BCBBDCDCABBCDCAADBCBDCAAB
BDDCDCBCABCCDDCDDDABCDABA
CCBBCCDBCDCDCCCDBBABBBBCB
AAABCCBCABAACCBBBBBACCADD
BCDCCCACABBDDCCADBDABDCAC
BXDXDCDCDBBDDCXBDCCCAXXXX
BCCCBBDCBDCDCDCCABAADCACB
BCCCDBDCBDDDCCACABADDCACB
BCDCXCDCABCDCBCBDACBCBDBA
BBCXBXBECBACDCDDAABBBXCXX
BCDCCCBCADDDCCBABDABACDBA
BBDCCCCCCBDDDCCCCCCBCDBCC
BCCBCCBCCDBDDCBBCBACABCBA
BCDCCCBCCBDDDBCDCCBACCCCC
CCDCCCACACCCCCCCCCCCCCCCC
462
783.
784.
785.
786.
787.
788.
789.
790.
791.
792.
793.
794.
795.
796.
797.
798.
799.
800.
801.
802.
803.
804.
805.
806.
807.
808.
809.
810.
811.
812.
813.
814.
815.
816.
817.
818.
819.
820.
821.
822.
823.
824.
825.
826.
827.
828.
829.
830.
831.
1675-18068
1675-18067
1675-18076
1675-18088
1675-18084
1675-18069
1675-18074
1675-18075
1675-18087
1675-18079
1675-18085
1675-18083
1675-18082
1675-18065
1675-18064
1675-18063
1675-18062
1675-18061
1675-18086
1675-18072
1675-18071
1675-18078
1675-18089
1675-18090
1675-18828
1675-18827
1675-18829
1675-18825
1675-18823
1675-18812
1675-18811
1675-18813
1675-18821
1675-18822
1675-18814
1675-18818
1675-18647
1675-18815
1675-18819
1675-18816
1675-18817
1675-18820
1675-18826
1675-18824
1675-18830
1675-18802
1675-18803
1675-18804
1675-18806
BADCDCDADCDAACCBCBACDBADC
BXXCXCXXXBDDDCXXXXXXBCXXX
BCBCCCBCABDCDCXDCDDCCCDBC
CCDCCCDCADBADBCBBBCCAAACC
BCCCCCBCABBDCCBABCACBABCA
CDBBDCBABDCBDCABBBBBBBBBB
CCBCACBCADADCCACDCDAAACBD
CDBCBCBCAACDCCABCCCCBCACD
CDDCCCBBABCDCACDCBBDBCBBC
BCDCCCBCABBDCCDCCCBACCCCC
BCBCCCDCABBBBBBCCCCBCDCAC
CACBCBBCAACDDCCDACADBAADA
ABDCBCBCCBCDCCADACADCDABC
BCCBDCDCCDCDCCCBCCABBDCAD
BBDBBCDADDCDCCBDCBABCBBCC
BCABCCDACBCCDCDDACBBCCABD
BCCDCABADBCDCCBCACABABBDX
BXCXXCBDCDCBDAXBBCABXXXXX
CDCEDCXCABACBDBACCBCCBDBA
BDBBCCBABBCBACBBCBACDBABC
BCDDCCBCAACACCBBBBBBBBBBB
CCDCDCCBBBBDCCCCCDDDBBBCC
BCCCBCBCACDDDCDBCCDBACADD
BCBCDCBCADCCCCABCBCBAABCB
BBDCCCBCABBDDCDCCADABCCCC
BCDCCCBCABBDDCCCCBCCBCABD
CDCDDCDCCBCDCCACDBCDCDADA
CDDBACDXBBCCDCCDCAAAAAACB
CCDCBCBCDBCDCCBAABBBAADCA
BBDCCCBCCBDADCDCCCCCCCCCC
BDDBCBDCCCBCXXACXBXDDXXBX
BCDCBCBCACBDCCXBCBDABCDXX
CDDCDCBDDCCDCCDCBXXCXBXXX
CDECCCCCCDCDDCACCCCCCCCCC
BAXXXCBAABCDDCCXXXXXXXXXX
BBABACBAAACDDADABCCDBBDBD
BDDCCBDBCBDCCBADCBCCCDDAA
BXDXXCDCCBDDCCXXBBCADDBBC
BDDXXCBCCXBCACXDXXAACXBAA
BCBCACBCCCCACCBDBCBCDBBBC
XXXXXCXCABDDCCXXXXXXBCACX
BCBCCCDCABCDDCBCCCCCCDACC
DCDDDCBCABBDDCCCCCCCBCABD
DCDCBCBCABADDCBACDBAAADDC
CXDCCCBCDBBDDCCDACBACDACC
BCCADCDADBCDDCABDADCBCBBD
BADCBCBCADCCCCCBDBCBCDABB
BCDACCBCABADBADBCCDABAADA
BBDCDBCBDBBDCCADCCBCBCDCA
463
832.
833.
834.
835.
836.
837.
838.
839.
840.
841.
842.
843.
844.
845.
846.
847.
848.
849.
850.
851.
852.
853.
854.
855.
856.
857.
858.
859.
860.
861.
862.
863.
864.
865.
866.
867.
868.
869.
870.
871.
872.
873.
874.
875.
876.
877.
878.
879.
880.
1675-18807
1675-18808
1675-18904
1675-18902
1675-18717
1675-18720
1675-18898
1675-18903
1675-18711
1675-18712
1675-18713
1675-18714
1675-18716
1675-18901
1675-18891
1675-18707
1675-18706
1675-18704
1675-18701
1675-18897
1675-18718
1675-18719
1675-18896
1675-18703
1675-18705
1675-18708
1675-18709
1675-18895
1675-18894
1675-18893
1675-18892
1675-18715
1675-18581
1675-18625
1675-18785
1675-18790
1675-18582
1675-18786
1675-18585
1675-18589
1675-18781
1675-18628
1675-18583
1675-18626
1675-18580
1675-18782
1675-18783
1675-18579
1675-18629
BDDCCCDCDBBADCBCCCCBCCDAD
BCBDDCBDBBBCDBADABCCCCDAD
BCDCCCBCACBCACADBBBBBBXXX
CBDBBBDCCDCBCAADBCAACDDCB
BCCACCBCABDDCCBBCCDDCCABC
BCDCCCEACBCDDCBBXBCXCDXCB
BCBCBCBCABCBDCCCACDABCDDA
BXDBCCBCABBDCCBCABBCCCCXX
CDCEACBBBBCAAAADCBAACBDAC
BDBBCCBCADBCCCBDCEEBABEAA
BCBCCCBCCBBDDCBDBCCBCBCBA
BCDCABBCDABDBBCBCDABCBCDB
BCDBCCBCABCDDDDXXXCABCBBC
BBDBCCBCAADDACADCCACBCCCC
BXCCDCDBDACDDCBCCCXACXXCX
CABCCCBEABCBCDBDBAAABCCDB
DDDCACBCABCBDCACBACBAACAA
BCDCCCBCABCDDCXXXXXXBXXXX
BBDABCBCAACACDCBDBCACACBA
ABBCCBACDACDDCACBACDCCADC
BXCCXCBXCBCDDCCXXXXABCBDB
BXCCDCDXXBBXDCXBXBDXAXDXX
CCBBBCCCCABBDDCCCCCCCBBBB
BDBCCCBCCBBDDCBCBCACCBCDA
BCDCCCCECCCCCCDDDDDDACCCC
CCCCCCBCCCCCBDACCXCXACCXX
CCADCBDCCCBADBACADBABCBDD
BDDCCCDCCACDCCABCADBXXXXX
CCBCDBBCBBDCCCDBBCCCBCDDC
CBBDDCBCCDCDCCADCCBABADCD
BCDCCCBCCBBDDCCCCCCCCCCCC
BCDXCCBCABDDCCXCXXBXCCCCC
BBBCCCBCADBCCCADBCBCCCBDB
BCDCXCBCAACDDCXBXXCXBCCAA
BBBCCCBCCCBACCCDACABCBBAC
BDDCCBBCDBCDDCDBBBABCCBBB
BDBDCCDCADDDDCDBCBCBDDCAA
BBBBBCBCABCABDDBCCBCCCCCD
BCCCADCCBDCDDCCCCCCBACADC
BADCBCDADDDCCCDCBBCCDCCBD
CDCCCCBCCBBDCCDBBBBBCCCCC
CEBDCBDCXBCDCCXDXCBABBBBB
BCDCCXXXXBBDDCDXXXXXCXXXX
BCBCCCBCABBDCCCDBCBADACCC
BCBADBCCDBBDDCCBBDCBCBBCA
CBDCCCCDCBDDDCDDDCCCCDCCC
BDDCADBCBXBDDCDCABDACAAXD
CADBBCDCDCCACDBBAAAACCDCC
BCDCCCBCCBDDBDCBCBBCABBBB
464
881.
882.
883.
884.
885.
886.
887.
888.
889.
890.
891.
892.
893.
894.
895.
896.
897.
898.
899.
900.
901.
902.
903.
904.
905.
906.
907.
908.
909.
910.
911.
912.
913.
914.
915.
916.
917.
918.
919.
920.
921.
922.
923.
924.
925.
926.
927.
928.
929.
1675-18623
1675-18587
1675-18621
1675-18627
1675-18622
1675-18636
1675-18784
1675-18787
1675-18590
1675-18586
1675-18584
1675-18789
1675-18173
1675-18174
1675-18176
1675-18177
1675-18178
1675-18172
1675-18171
1675-18169
1675-18168
1675-18167
1675-18161
1675-18162
1675-18154
1675-18305
1675-18151
1675-18152
1675-18304
1675-18166
1675-18165
1675-18164
1675-18163
1675-18159
1675-18157
1675-18156
1675-18155
1675-18158
1675-18153
1675-18160
1675-18267
1675-18266
1675-18259
1675-18268
1675-18180
1675-18269
1675-18242
1675-18246
1675-18245
BBDXBCDCBDDDCCDCACXBDXBBD
BDDBCCDCADCDDCCDABCCDCDCC
BCBCDCBCABCDDDAXXXXXDCCDX
BDXXXCEXCBBDCCXXXXXXEXAXX
BDDCCCBCABCDCCCCCABBBBCCA
BCDCBCDCBBBDDCCDBDCAXXXXX
BCDCBCDCAABDDCCCCCCCCBDCC
BDDBCCBECBCCDCDCCCBCBDCCC
BBCCBCBCABCDDCBBCCDCBBBCB
BDDCBCBAADBBCBBCCBCACADAD
BCDBDCBCABDDDCDBDDACCCDCB
CCBCCBBBBDDABCXDCDCBCCBDC
BBDCCCBCADDBDCDCCCCCCADDD
BCACDCBCADCBDCCACXXXXXXXX
BCDCCCDDCBDCCDDDCCCADBDAC
BCBCCCAACACDCADBBAABDADAC
BCDCCCBCABCCCDBCBDABAADBC
BCDCACDCCDDDDDBDBACDBCABC
BBBCXCBCABCDDCCDCCAADCDAC
BCDCCCBCCACACACCACCCCCACC
CCDCDCBCCDBADCCDCDACDCCDC
BCBBCDDDACBCBDDDACBACABCC
BDDCBCDCDDCDDCACCDCACBDCA
BCBBCCBCABCEBABCEABDCCADD
BBBXCBDBCAAADDACACACXXXXX
CCDCBCDCCBBDDCDBAAABBADAC
CCBADCABADCADCCBDBDBDBDAC
CXDCDCACADBBDCBACBDDBCDBC
BADXXBCBDBDCDCBDXCBAXXXXX
BDDBDCBDABDBDCCCBCBACBDCD
BADBACCCCBCAABCBCBCBCDCAB
BDDXCCBCABDBCCDDBCCCCDBCB
CCDCDCBCABDBDCCBCBACCBCBA
CBBBBCDDCCBCCCBCBDCBCBCDB
BDDDACBCABBADCCBBDCDBCDAB
CBDCACDCDADBDCBBDCABBCBDC
CCBCCCCCCBCCDCCCCCCCCCCCC
CXBXCCBCADBDCCBXCXXBAACCA
BCBDBCCBCDCBCCCDBCACDACBA
BBBXCCBCAAAADDACACAXBCACX
BCDCACDCBBBAADCCCBDACBDDD
BBDCACBCBACBBDBCDBCBDEBCA
DCDCBCDCACDBCCBCDCAACACCD
BCDCCCBCABCDDCBCBCCADCBBD
BCCCCCBCABDDBBCABDCABCBDA
BCDCCCBCABCDDCBCBCCABCBBB
BBDCCBCCABCADCDCBCABACBCA
BCACDCDCABCDBCABACCBCBCBA
BCCADCCBABBADXBCADBCBCADB
465
930.
931.
932.
933.
934.
935.
936.
937.
938.
939.
940.
941.
942.
943.
944.
945.
946.
947.
948.
949.
950.
951.
952.
953.
954.
955.
956.
957.
958.
959.
960.
961.
962.
963.
964.
965.
966.
967.
968.
969.
970.
971.
972.
973.
974.
975.
976.
977.
978.
1675-18243
1675-18254
1675-18256
1675-18257
1675-18258
1675-18260
1675-18244
1675-18263
1675-18264
1675-18255
1675-18241
1675-18247
1675-18248
1675-18249
1675-18250
1675-18252
1675-18251
1675-18253
1675-18270
1675-18265
1675-18311
1675-18261
1675-18262
1675-18301
1675-18170
1675-18710
1675-11687
1675-18117
1675-18131
1675-18179
1675-18691
1675-18678
1675-18046
1675-18788
1675-18624
1675-18228
1675-17103
1675-18801
1675-18805
1675-18048
1675-18058
1675-18281
1675-18034
1675-18056
1675-18055
1675-18053
1675-18286
1675-18031
1675-18044
BCDCDCBXXDCBCCDXAXADACABD
BBDCCCBCADBDCCDCDCBCCDBCD
BCDCCCDABCDCCCCCBCCACCDAB
BCBCDCBCAABCDCDBBBBBCAAAC
BBDCBBBBBBCDBCDDACBABBBBB
DBBBCBDCDXBXCBCCDCBDCBCXB
BBDCCCDCCCCDACCBDBAACCDCC
BXDCBCBCABCDCCCCBCBXCDACD
BCDCDABCDACCDDDAXXXXDCXXX
CDBBCBBDBBBBBBBBCBABDDBDB
CCBBBCCACBCDCCCCCCCBCDACB
CXDBCCBCEBCCCCCBBDCABACDC
BCDCXCXCXBCDDCXXXXXXBCXBD
BCDCDCBCABXDDCCBCCBCCCCBC
DCDCCDBCCBBDCCDCBBCBCBCDC
BDDCCCDDCBBCDCDCBCDCBCBXC
BDCBDCBCADCDCCBCBDABCBDBA
BCDXXCCCDXXXXXBXXXXXDCCBB
BBDDDDDDBBCDDCABBBBBCCABD
BCADBCDCDDCDCCBAADBBBCBDA
BCCBCCDACBCCDCCBACACCBBCD
CCBCCCBCABDDCCCCCCCADADCA
BCDCACBCADCADAAACBDCDDCXX
BCCXDCDCADCDDCBBCCCXAAAXX
BCDBXCBCABCDCCDXCCCXACCCD
BCBACCDCDCDBDCDCCCBBCCBBB
BCDBDCBCABCDDCCCBDACCCABD
BCCCCCDCCBBDDCCCCCDDCCCBB
BCDCCACBBBCDCCBDACBABBCBA
BCDDCADCBBDDDCDDACBABCBBC
BCDCDCBCABBCDCBDCDBACCBCD
BDDCCCBCABCDDCADBCBAXXXXX
DBCBABDBCBAADCBBBDCCCCCCC
BBDCCCBCABDDDBDDABBBAABCC
BBDCCCBCABCCDCBDCBBCDCBDC
BCDCBCBCABCDDCCXBCBXBCABB
DDDDBBDBCBACCAACCEDCBDCCA
BDDCCCCCCBBDCCCCCCCCBCABC
BCDCCCAAABBDDCCCCDBCCCCCC
CCCBABDBCBBCDCCAAAAABBBBB
CADABBDAADBCCADABCEABBADA
ABCBADBXCAACDAAXCADCABBDC
ADDBCABCBACACABCCCACBABBA
ADCCDBDBCADCXBDCCBCCBDCDX
ABBCABDDCDCACCBCCADCAAACA
BBBBBBDBCCBCDBDCCDDCCCCCC
CDDBCBDCCADDDBDBAABCBCBCA
CBCCDDCABACADBBCCCCAACBBD
CDDCDBDBCCAACCACBDBABCBDA
466
979.
980.
981.
982.
983.
984.
985.
986.
987.
988.
989.
990.
991.
992.
993.
994.
995.
996.
997.
998.
999.
1000.
1001.
1002.
1003.
1004.
1005.
1006.
1007.
1008.
1009.
1010.
1011.
1012.
1013.
1014.
1015.
1016.
1017.
1018.
1019.
1020.
1021.
1022.
1023.
1024.
1025.
1026.
1027.
1675-18051
1675-18045
1675-18285
1675-18050
1675-18283
1675-18041
1675-18042
1675-18043
1675-18052
1675-18060
1675-18057
1675-18284
1675-18054
1675-18049
1675-18282
1675-18033
1675-18059
1675-18032
1675-18209
1675-18204
1675-18203
1675-18202
1675-18201
1675-18192
1675-18200
1675-18184
1675-18186
1675-18206
1675-18210
1675-18207
1675-18188
1675-18303
1675-18196
1675-18197
1675-18195
1675-18187
1675-18190
1675-18198
1675-18199
1675-18193
1675-18208
1675-18185
1675-18183
1675-18205
1675-18181
1675-18191
1675-18189
1675-18194
1675-18861
DCCCABDBCACCDCBCCCACBBCCC
DCCCCBDBCAAACADDABCCCCCCC
ABAACABBCAACCBCBDCBCCBDAA
BBBBBBDBBCBADABCBBBBAABBB
EBACABDBCEBDDXCXCBDCBADCA
ACBABAACACDADABBABCACBDBA
AAAAABDBCADBDCACCCDCBBBBB
CBCACBDBCDACDABACDABDACAD
CCCBABDBCAAACCBCBBBDBBCBD
BDACBBDBCDAABACBCABCCBABB
ACDBABDBCDCDBCDBCDDADBCBD
BACCCBDBCCCADCBCBDCABCCBA
BCCBCBDBCBCCDCBBDCBCBCCBC
ACDDCBDBCXCABCCXDXXCCCBAC
ACCADDDCCACCBDDBCABDCADAA
ADDBCDBCCCDADCBBCCCCCBBBC
BCBABBDBCCCADCBACADCBBCAB
DABBBABACBABCCAACCDCACBCA
BDCBCCDCCBDCDABCDABDACBCD
BCDCCBBCCBBDDCDABCBCDABCD
BCDBDCDCABCDDCDDBCBCBDCBC
BCDCCCBCABCDDCBCDACBCCBAD
BBABDCBCCDDDCCDDBBBABBBBC
BCDCCCBBDBCADCAAADACBCBDB
BCDXCBDEXCBAAXDCAXBAXXXXX
BDDCDCBCADCBDCBDACBADBBCD
CXDCCCDCCDBDCCXXXCAAXBXCX
BCDBDCBDCBDCCCBDBBBABBBBB
BCDCCCBCABBDDCCAXXXABXBXX
BDDCDCDACDBBDCACBCDAABADC
BCDCDCBCABCABBDCBBCDBCCCC
BDDBCCBCADCBDCDDCBCDCBCDB
BBDCCBBBBBCDCCBBBBBBBBAAD
BDDCCCCCCBBDDCDDACBACCCCC
CCCCCABCDBDDDCDCCBCBBCDCC
BCDCCBBBBCCCDCADADAAXXXXX
DDCXXCBCCCCDDCBBCADXCDDBA
BCBCCCBAXBBCBCXXXXXXBADBD
BBDBBBBBBBCDCBBBBBBBDBBBB
BDDBCCBCADCCDABBCCBBCBCDB
BCDCBCDCCBBDCCBBBBBBBDDDD
DCBCBCBCDDCACCCDCDBBCBBCB
XXDXCCDACDXBXACXXXXXXXXXX
BEEBBCDCACCXXCCXXXXXXXXXX
CBBCABDBCBCADABCCXXCBBACC
BCDDACDCABBCCCCACCCABCACD
BBDCBCBCDBCCDCAXABAXCCXDB
AXBCDCDACBCDDBXXBXXXXXXXX
BCDBDCACCDBACCBBDAAACDABC
467
1028.
1029.
1030.
1031.
1032.
1033.
1034.
1035.
1036.
1037.
1038.
1039.
1040.
1041.
1042.
1043.
1044.
1045.
1046.
1047.
1048.
1049.
1050.
1051.
1052.
1053.
1054.
1055.
1056.
1057.
1058.
1059.
1060.
1061.
1062.
1063.
1064.
1065.
1066.
1067.
1068.
1069.
1070.
1071.
1072.
1073.
1074.
1075.
1076.
1675-18870
1675-18862
1675-18859
1675-18851
1675-18865
1675-18849
1675-18863
1675-18921
1675-18864
1675-18923
1675-18858
1675-18857
1675-18869
1675-18866
1675-18924
1675-18922
1675-18925
1675-18848
1675-18926
1675-18835
1675-18847
1675-18846
1675-18845
1675-18844
1675-18843
1675-18841
1675-18831
1675-18842
1675-18832
1675-18833
1675-18834
1675-18836
1675-18837
1675-18838
1675-18839
1675-18840
1675-18143
1675-18300
1675-18299
1675-18037
1675-18040
1675-18038
1675-18039
1675-18017
1675-18015
1675-18016
1675-18014
1675-18013
1675-18011
CDDCCCBCCBBBCCBBCACBXXXXX
BBDCDCBCADBBDAABCBDABDACD
BXDCBCXXXBDDCCXXXXXXBCXXX
BXCCDCBCCCCDDCBCCBCCBCBCC
BDAACBCAADDBDBABAAAACBDCB
BCDCDCBCABBDDXXXXXXXBAXDC
BCDCDCBDCBBACCCCBBADDADCC
BCDXCXXXXBBCCCXXXXXXCXDXX
BDDCCXXXXDCCCCBXXXXBXXXXX
BDDCCCBCABDACCCABCDACBDBC
BCDADCDCABCDDCAXXXXXCDCBA
BBDCBBDCCBCDDACBAABCBBCAA
BDCCDCBCABCBDCBCBBCCCBCBC
BCBCXADCCDCDCCXBXCBACACCC
CCCBDCDAABCDCCCBCCABCXCXX
BDCDCCCBADCDDCCACDBDCCACC
BCDDCCDCCBCBCCDCDDCDBCBBD
BCDCCBBCCBCDDCCCCCBADDCDC
BCDDDDCCCCCAACBBABAABBCAA
BCDCDCBACBCDDCDDABBDCDDCC
BCBXBCDCBCBDDCXDCCADXBDDC
BDDCBCDCBBDACCDCCCCCBCBBC
CBBCBCBCBDCDCCABBCCBCCDCA
BDDCBCBCDBDDDCACBCBDCCBCA
BDDCCCBCCBDDDCAABCABCABCA
DCDCCCAAADBBDBCBACAACAAAC
BCCCDCDCDADCBCCBADCBCCDAB
BBCBBCBCCCBCBCABBBCCCBBBC
CDCBDBDACCCCCCBDCAAADBCDC
BCBDDCADCDBDCCDBCDCBCABBC
BCDCDCBACBCDDCDDABBDCDDCC
BDDCBCXBDBBBACBBBBCCDCCDD
CDDCCCBCCBDBBCCBBBBBCCCCC
CDCCCDBCBBCDDCCBDABCACCCB
BCDCBCBCABDCCCDDCDCBBBDAB
BCDCDCBCABDDCCBDBADBCBCBC
BBBACCBCCBBCCCABCACACBADC
BECBCBBBDBBDDCECBCADBCCBC
BCBCCCBCDBCCDCBDBCDCBCBCB
BCDCCCBCABBDCCBBCBBCBCCDB
BCDCBCBCACCBDDBCBDCCDDCBB
BCDCCCBCDBCADCCDBBCBDBBAC
BBCBBCBCABCDCCCDBBBBBBBBB
CBDXBCDDXCCABBABCXACCBCDD
CDDCBCDCBCBCBACBCBCBBBCBC
BCDCDCDACBCDCCBXDXBACCCCC
CCDCACDEACBBDCCDDCBADCDAB
BCDDCAABBCACDABACAACACBCA
BDDCCCBBCCCCCCACCCCCCCCCC
468
1077.
1078.
1079.
1080.
1081.
1082.
1083.
1084.
1085.
1086.
1087.
1088.
1089.
1090.
1091.
1092.
1093.
1094.
1095.
1096.
1097.
1098.
1099.
1100.
1101.
1102.
1103.
1104.
1105.
1106.
1107.
1108.
1109.
1110.
1111.
1112.
1113.
1114.
1115.
1116.
1117.
1118.
1119.
1120.
1121.
1122.
1123.
1124.
1125.
1675-18144
1675-18020
1675-18142
1675-18019
1675-18223
1675-18240
1675-18221
1675-18231
1675-18234
1675-18237
1675-18238
1675-18226
1675-18218
1675-18219
1675-18216
1675-18232
1675-18233
1675-18235
1675-18220
1675-18230
1675-18239
1675-18236
1675-18227
1675-18222
1675-18211
1675-18224
1675-18225
1675-18212
1675-18213
1675-18214
1675-18215
1675-18217
1675-18229
1675-18631
1675-18665
1675-18667
1675-18633
1675-18670
1675-18659
1675-18646
1675-18635
1675-18656
1675-18669
1675-18664
1675-18634
1675-18657
1675-18653
1675-18666
1675-18658
CCBCCACBCADDDCDCDCCBADBCC
BBBBCCDCAXXXXBXXXXXXBDCCC
BCDCCCDCDBBDDCACBCADCBACB
BCDCCCDCCBCDDCDCBBBBBBBXB
BDBCACBCCDCDDCABADXXCCDCD
CDDBXCBDDBCDDCADXAADDADCA
BDCCBCDACDBACCCBDCBACABCD
CDDBBCBDCBCDCDABCAACBDCCA
CCCDCDBABCACCCABBCAACDACD
BBDCCCBDEBDDCCCBBCBABCXBD
BBDCCCBCAACDDCBDDCDCDBDDC
BDDBXCBCABCDCCXXXXXXXXXXX
BCBDCBBCABCDDCXDCABXCBBCX
BCCCCCCDCBBDDCCBCCDBCCDCC
CABCDCBCADBACCCCBDACBCDBC
DBBCBCBCCDBDBCAAADCDBBBCC
CDDCDCBCDDCBDCACBCABCDCBA
CCDCDBBBBCDBDDACCCCCDCCCC
BCDBCCBCABCDDCDABXCCBCCCA
CDDBCCBCABBBDCBBBBBBCBBBB
BBDCCCBDEBDDCCCCBDBABCCBB
BCDCCCBCCBCDCCDCCBDCCBDCC
BDDBCBDCBBCDCBBCBCDACBCAC
BBDCCCCCCBCDCCCCCCCCCCCCC
BCCDBCBCDBDDCCCDBCBABCCAB
BBBCCCBCCBCDDCCCDDDDBBBBB
BXXXACDCCXCBBCXXXDXXXXXXX
BCDCBCBCABDDDCDACBCADBCCA
BDBCDBDCBBCDCCDDDADCCDDCC
BCBCCCBCAXCCDCDCCCCCDCCCD
BCBCBCBCABCDDDDDADBDACDDC
BCDCCCBCACADABCBBCCDABCCD
BBDABDBDADABDBBCACBADBABC
BDDDCCBCCBCDDCCAXCDADDDAC
BCDBCCDCABBDCBBCCCBBDBBBB
CADBDBDCABADABBCDACDACBDA
BCDDACBCADCCBCCAACABABCCC
CDBBCCXCADCCDCCCCDCCAXDDC
BDBCDCCABBCDBCBBABAACDCBA
DCDBCCBCADBDDCBCBCBCBCBCB
CBDBACDCAADACCCBDCBCEBDAC
CXBCCXXXXXXXXXXDACBAXXXXX
BDCBACBABACDCCADACBAACADD
BBDCCCCCCBCDDCDCCCCCCCCCC
BDDCDCBBCBBDCCDCBBDDBCCDB
DCBDACBDDBCDDCDCCBCBDCAXX
BCDCCCDCCBCDCCCBCCDBCBCAD
BDCCCCBCCCBDDCDCBCDCCABCC
BCDDACBCCBBDBCABCDABCBCDB
469
1126.
1127.
1128.
1129.
1130.
1131.
1132.
1133.
1134.
1135.
1136.
1137.
1138.
1139.
1140.
1141.
1142.
1143.
1144.
1145.
1146.
1147.
1148.
1149.
1150.
1151.
1152.
1153.
1154.
1675-18632
1675-18654
1675-18645
1675-18655
1675-18663
1675-18649
1675-18644
1675-18643
1675-18642
1675-18650
1675-18662
1675-18660
1675-18641
1675-18651
1675-18652
1675-18668
1675-18272
1675-18276
1675-18273
1675-18120
1675-18280
1675-18119
1675-18100
1675-18277
1675-18274
1675-18096
1675-18095
1675-18275
BACBCCBCBBCDDCCCBACCCACDA
DDDCBBBCADCCDCABBBABBCBCA
CBDBAABCBBCAECAABCDEBCBBB
CDDBDCBCACCBDCCXBCACACBDC
CCBCCCBCABCACCCBCXADCACAC
CDCCDCBCABCDCCBCCCCCAABBC
BCDCDCDACBCDDCCDDBCBCBBBB
BCCCDCBADBBCCCBABCDBCDACA
BDDCDCBADDCDDCBBABBBDABBC
BDDBBCDCCCCCDCACBDCCBCDCC
BBCBBCBBCDCBDCCBBBBBCCCBB
BCDCCCDCCACDADACCCCCCCCCC
BCCCDCBCCABDBDCBAXXBXAXXC
BDDBCCBCABCDDCCCCBABCBDDA
BCDBCCBCDDCDDCBCABCABCBAD
CCBCDCACAADCDCDCCCCCCDADC
BBDBCCBCABCACCADBCBDAABDA
BADCCCDACBCDDCCCADCBBCDBC
BBCBCCDCBCBBBCCBDCCBBBCCB
BCDCCCBCDACDDCABACBACCDBA
BADBDCBDAABDDCCBDACBACABD
BCDBACBACCCDDDABCBADCBDCB
BCDCCCCDDBCDDCDDDDDDBDDDD
BCCBCCBCABDCDCBCBBBCCBACD
BCBACCBCADADBCDCBBBBBBBBB
BDDCCCBCDBCCDCBBDDCAACCDB
CDBBCCBDDBCACCDCBBCCBXCBC
BBBCDCBCABBDCCDBBBBCBCBBB
1155.
A test taker x is administered the adaptive test. His initial ability is assumed as 2.0.
Accordingly, he is given the first items #5 with difficulty value of 0.340. He answers it correct
and the next item administered is of difficulty level 0.880. The process is continued till he
answers an item with difficulty value of 1.970 as incorrect. The test is terminated and his final
ability is estimated at 2.531 as shown below.
470
Test Taker X administered with the Adaptive Test
Item
No
B
u
θ
5
18
9
22
0.340
0.880
0.990
1.130
1
1
1
1
2.0000
21
1.970
0
Item
No
B
u
θ
5
18
9
22
0.340
0.880
0.990
1.130
1
1
1
1
2.473
21
1.970
0
Item
No
B
u
θ
5
18
9
22
0.340
0.880
0.990
1.130
1
1
1
1
2.529
21
1.970
0
Item
No
B
u
θ
5
18
9
22
0.340
0.880
0.990
1.130
1
1
1
1
2.530
21
1.970
0
p=1/(1+e(θ-b)
)
q=1p
0.190
0.326
0.364
0.419
0.8402
0.7540
0.7330
0.7047
0.160
0.246
0.267
0.295
0.970
0.5075
0.493
e-(θ-
p=1/(1+e(θ-b)
)
q=1p
0.118
0.203
0.227
0.261
0.8941
0.8310
0.8150
0.7930
0.106
0.169
0.185
0.207
0.605
0.6232
0.377
e-(θb)
b)
p=1/(1+e(θ-b)
)
q=1p
0.112
0.192
0.215
0.247
0.899
0.839
0.823
0.802
0.101
0.161
0.177
0.198
0.572
0.64
0.364
e-(θ-
p=1/(1+e(θ-b)
)
q=1p
0.112
0.192
0.215
0.247
0.899
0.839
0.823
0.802
0.101
0.161
0.177
0.198
0.572
0.64
0.364
e-(θb)
b)
u-p
p*q
0.160
0.246
0.267
0.295
0.507
0.461
0.134
0.185
0.196
0.208
Correction
Factor
Next
Estimate
0.473
2.473
Correction
Factor
Next
Estimate
0.056
2.529
Correction
Factor
Next
Estimate
0.001
2.530
Correction
Factor
Next
Estimate
0.001
2.531
0.250
0.973
u-p
p*q
0.106
0.169
0.185
0.207
0.623
0.095
0.140
0.151
0.164
0.044
0.785
0.235
u-p
p*q
0.101
0.161
0.177
0.198
0.636
0.001
0.091
0.135
0.145
0.159
0.231
0.762
u-p
p*q
0.101
0.161
0.177
0.198
0.636
0.001
0.091
0.135
0.145
0.159
0.231
0.762
471
Given below is the set of calculations for an adaptive test 25 by 999 by 1 Parameter Rasch
Model. The b values are arranged in 6 categories as indicated and adaptive testing modules
are created and sample calculations of final ability and true scores for a set of responses from
a test taker.
Illustration of an adaptive test for a parent test of 25 by 999 after analyzing through BILOGMG single parameter model with b values and consequent adaptive testing modules and an
illustration of calculating final ability and true scores as if the test taker has taken the parent
test. Click Here
An alternate method of estimating the final ability through Prior and Posterior Distributions is
also illustrated here. Click Here
The author takes the opportunity of a new learning along with his team; Ruchika Girdhar,
Neha Jain and Prachi Tyagi, that the use of Benjamin Wright mathematical formulation
illustrated above with iterations to arrive at a final ability is perhaps the easiest way to build a
CAT ability estimate algorithm. With the provision below that the second incorrect response
may be used as a termination criteria for terminal rule for CAT and the Benjamin method
indicates the true ability estimate within a couple of iterations or a consistent limit of the
correction factor of 0.001.
Future of Item Response Theory in India
Many testing, Assessment, Councils and National Bodies in US including Educational Testing
Service (ETS), College Entrance Board (CEB), American Psychological Association (APA), US
Civil Service Commission and other recruitment agencies have been using IRT for the last few
decades. In Particular Rasch Model of Analysis have found applications in other domains
other than Testing and Assessment like Medicine, Textile, Aeronautics and Manufacturing
Industries where very accurate results are required. There is evidence that nearly 525
organizations in the US, UK, Germany, Japan and China are actively using IRT methods of
analysis for extremely accurate results. The 3 parameter Logistic model has been in use for
several decades in Educational and Training Institutions and IRT continues to be a domain of
research for Scholars in Measurement, Evaluation and Assessment. In India, the author and
several of his Doctoral Students are using IRT in Admission, Entrance and Advance Placement
Tests. In recruitment test MeritTrac is the pioneer in using IRT particularly Adaptive Testing
Modules, primarily driven by clients and customers who increasingly demand quick and more
accurate results.
There are several domains in which IRT can influence a future of Testing and
Assessment in India. Some of these are:
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1.
2.
3.
4.
5.
6.
Achievement Testing
Recruitment Testing
Adaptive Testing
Mastery Testing
Scholarships and other Award Testing
Diagnostive Testing
These applications in these domains are explored below.
Achievement Testing
Following increasing demand for very accurate measurement, evaluation and assessment,
School Boards, Universities and other Certifying Organizations are driven to the use of smaller
length test and increased accuracy and efficiency test. Many organizations mentioned above
are using Question /Item bank for constituting for both formative class room test and for final
end examinations. Various Question/ Item bank questions and items are calibrated using IRT
and ascertaining invariant Item parameters and incorporated in the Question/Item bank for
future use. A healthy trend is being seen in Universities and Institutions of Higher and School
learning and increasingly being utilized for mass scale examinations.
Recruitment Testing
Recruiting Agencies in India are being compelled to make use of smaller length and shorter
duration test and at the same time yielding better, accurate results. And they are increasingly
introducing computer aided Adaptive Testing Modules and other online instruments. Even
though its application in India from recruitment has just begin, there is increasing
opportunities for recruitment in BPO and ITES sectors where a very large number of aspirants
compete with the smaller number of positions. The time at the disposal of several Industrial
and Training Organizations is very limited for conducting test for assessment of Knowledge,
Skills and Attitudes required for the various positions in the industry. IRT can find applications
in Classical Test of Recruitment with calibrated item characteristics to yield accurate results
wherever and whenever, timeline is not restricting factor. As reiterated earlier where the time
at the disposal are very short and more accurate results are needed, IRT driven computer
aided Adaptive Testing Modules and Instruments can be effectively put into use.
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Adaptive Testing
This particular application of IRT is extremely promising. In Recruitment, Admission, Entrance
and Awards Testing for the simple reasons that it calls for a smaller length test for very short
duration (MeritTrac is contemplating to use a module of 6 items and 8-10 minutes duration).
The author has devised a simple procedure to conduct Adaptive Testing in offline/ paper-pencil
test. According to him a sufficient number of calibrated number through IRT are coded and
stored in an Item Bank on a computer and classified into groups or categories of items of
different item difficulty ranges(-3 to -2,-2 to -1,-1 to 0,0 to1,1 to 2,2 to3) yielding 6 groups.
For any test taker wanting to take an Adaptive Test is prescribed to take 1 item from each
group which enables that test taker of any ability level to miss 1, 2, 3 or 4 items of the test.
The author has classified those missing 4 of the 6 items, 3 of the 6 items, 2 of the 6 items and
1 of the 6 items as being taken as “Below Average”, “Average”, “Good” and “Par excellence” of
their initial ability level before taking the test. Accordingly in the estimation of test takers final
ability an initial assumed value for the test taker for successive ,approximation of ability
estimation are respectively taken as -0.5,0,1 and 1.5. Benjamin Wright’s final approximation
using maximum Likelihood estimate is made use of as elaborately discussed elsewhere in the
e-book.
Mastery Testing
It is found in many assessment scenarios that in Certification or Categorization of achievers in
a dichotomous fashion like traditional Pass/ Fail, Selected/ Rejected and Maser/ Non Master,
Mastery testing is resorted to. This is a result of Carroll and Bloom’s research work for years
that yielded the concept of Mastery Testing and Mastery Learning. This is a particular case of
an achiever who can be certified as a Master or Non master. A usual level of Mastery is
prescribed as 90/90 which indicates 90% of test takers will secure 90% in the test. There are
also situations where 100/100 is insisted, particularly in Nurses Certification Test where 100%
Mastery is eminent and required (example, nurse is to be certified for distinguishing between
Poisonous/Non Poisonous materials).
Scholarships and other Award Testing
IRT calibrated items in relation to item characteristics related to item difficulty, item
discrimination and item guessing provide a platform to constitute a special test for award of
Scholarship for any other Excellence awards. It has to be understood that items in a bank
calibrated with IRT parameters will enable sorting out the items and the order of increasing
difficulty and discrimination and as far as possible we can sort out items with high difficulty
values ranging from 2 to 2.5 with very high to perfect discrimination so that they can serve the
requirements for a scholarship test. Those who perform very well on these and their ability
estimates and true scores are beyond the accepted cut off for award or Scholarship may be
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selected for such awards. IRT thus provides a test with items all of them aimed at a cut off of
difficulty and discrimination required for such awards. This is an application which is worth
attempting for such awards as Award of Foreign Scholarships, NIIT’s “Bhavishya Jyoti
Scholarship” and the like.
Diagnostive Testing
Educationists and Trainers all over the World are now a days increasingly providing feedback
to Students and Trainees on the strengths and weaknesses of their performances in terms of
content areas, Abilities and Skills tested and levels of difficulty of items. It is therefore possible
with IRT calibration and coding adopted for items in terms of content, ability cluster and
difficulty levels to sort out items from different content areas, from different clusters and from
different levels of difficulty. It shall then be possible to generate a feedback that will list
strengths and weaknesses in respect of selected contents, selected clusters and selected levels
of difficulty. Thus weaknesses in these areas can be diagnosed and on the basis of these
remedial steps can be recommended. This is an area of application that needs to be tried at all
levels of Education and Training. In particular by teachers and trainers on a continuous basis.
Future of IRT in MeritTrac
MeritTrac has already started using an adaptive test module for traits like analytical ability
verbal ability attention to details etc. Making use of a single parameter Rasch model.
Maximum likelihood estimates as propounded by BenjaminWright is made use of. After a few
years of experience the two parameters and three parameters model will be made use of. At
the same time items in the item bank will be coded with IRT item parameters for future use.
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APPENDIX
BIRT Software
http://echo.edres.org:8080/irt/baker/software.htm
Adaptive Testing Tutorial
http://echo.edres.org:8080/scripts/cat/catdemo.htm
Applets for use
1. Applet1( for illustration)
http://www.metheval.uni-jena.de/irt/ptb.html
2. Applet2
http://www.metheval.uni-jena.de/irt/ii1pl.html
3. Applet3
http://www.metheval.uni-jena.de/irt/trf1pl.html
4. Applet4
http://www.metheval.uni-jena.de/irt/sem1pl.html
5. Applet5
http://www.metheval.uni-jena.de/irt/abi1pl.html
6. Applet6
http://www.metheval.uni-jena.de/irt/MLE.html
7. Applet7
http://www.metheval.uni-jena.de/irt/Finale.html
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8. Applet8
http://www.metheval.uni-jena.de/irt/bbit.html
9. Applet9
http://www.metheval.uni-jena.de/irt/trf2pl.html
10. Applet10
http://www.metheval.uni-jena.de/irt/iif2pl.html
11. Applet11
http://www.metheval.uni-jena.de/irt/tif2pl.html
12. Applet12
http://www.metheval.uni-jena.de/irt/sem2pl.html
13. Applet13
http://www.metheval.uni-jena.de/irt/ml2.html
14 Applet14
http://www.metheval.uni-jena.de/irt/all2pl.html
15 Applet15
http://www.metheval.uni-jena.de/irt/irf3pl.html
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Basic Principles of IRT And Application to Practical

Transcription

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