RDocumentation
Moon
Learn R
Search all packages and functions
⚠️
There's a newer version (3.17) of this package.
Take me there.
catR (version 3.5)
Procedures to Generate Patterns under Computerized Adaptive Testing
Description
Generation of response patterns under dichotomous and polytomous computerized adaptive testing (CAT) framework.
Copy Link
Copy
Link to current version
Version
Version
3.17
3.16
3.15
3.14
3.13
3.12
3.11
3.10
3.9
3.8
3.7
3.6
3.5
3.4
3.3
3.2
3.1
3.0
2.6
2.5
2.4
2.3
2.2
2.1
2.0
1.6
1.4
1.3
1.2
1.1
1.0
Down Chevron
Install
install.packages('catR')
Monthly Downloads
5,466
Version
3.5
License
GPL (>= 2)
Maintainer
David Magis
Last Published
September 27th, 2015
Functions in catR (3.5)
Search functions
MEI
(Maximum) Expected Information (MEI)
tcals
Items parameters of the TCALS 1998 data set and subgroups of items
simulateRespondents
Simulation of multiple examinees of adaptive tests
EPV
Expected Posterior Variance (EPV)
startItems
Selection of the first items
integrate.catR
Numerical integration by linear interpolation (for catR internal use)
semTheta
Standard error of ability estimation (dichotomous and polytomous models)
genPattern
Random generation of item response patterns under dichotomous and polytomous IRT models
genPolyMatrix
Item bank generation (polytomous models)
randomCAT
Random generation of adaptive tests (dichotomous and polytomous models)
genDichoMatrix
Item bank generation (dichotomous models)
Pi
Item response probabilities, first, second and third derivatives (dichotomous and polytomous models)
nextItem
Selection of the next item
test.cbList
Testing the format of the list for content balancing under dichotomous or polytomous IRT models
eapEst
EAP ability estimation (dichotomous and polytomous IRT models)
MWI
Maximum likelihood weighted information (MLWI) and maximum posterior weighted information (MPWI)
thetaEst
Ability estimation (dichotomous and polytomous models)
OIi
Observed information function (dichotomous and polytomous models)
Ii
Item information functions, first and second derivatives (dichotomous and polytomous models)
testList
Testing the format of the input lists
eapSem
Standard error of EAP ability estimation (dichotomous and polytomous IRT models)
Ji
Function $J(\theta)$ for weighted likelihood estimation (dichotomous and polytomous IRT models)
KL
Kullback-Leibler (KL) and posterior Kullback-Leibler (KLP) values for item selection
breakBank
Breaking the item bank in item parameters and group membership (for content balancing)
GDI
Global-discrimination index (GDI) and posterior global-discrimination index (GDIP) for item selection