Learn R Programming
⚠️There's a newer version (3.17) of this package.Take me there.

catR (version 3.6)

Procedures to Generate Patterns under Computerized Adaptive Testing

Description

Generation of response patterns under dichotomous and polytomous computerized adaptive testing (CAT) framework.

Copy Link

Version

Install

install.packages('catR')

Monthly Downloads

1,370

Version

3.6

License

GPL (>= 2)

Maintainer

David Magis

Last Published

January 2nd, 2016

Functions in catR (3.6)

semTheta

Standard error of ability estimation (dichotomous and polytomous models)
test.cbList

Testing the format of the list for content balancing under dichotomous or polytomous IRT models
MEI

(Maximum) Expected Information (MEI)
eapEst

EAP ability estimation (dichotomous and polytomous IRT models)
tcals

Items parameters of the TCALS 1998 data set and subgroups of items
GDI

Global-discrimination index (GDI) and posterior global-discrimination index (GDIP) for item selection
integrate.catR

Numerical integration by linear interpolation (for catR internal use)
thetaEst

Ability estimation (dichotomous and polytomous models)
breakBank

Breaking the item bank in item parameters and group membership (for content balancing)
Ji

Function $J(\theta)$ for weighted likelihood estimation (dichotomous and polytomous IRT models)
startItems

Selection of the first items
eapSem

Standard error of EAP ability estimation (dichotomous and polytomous IRT models)
OIi

Observed information function (dichotomous and polytomous models)
genPattern

Random generation of item response patterns under dichotomous and polytomous IRT models
genDichoMatrix

Item bank generation (dichotomous models)
MWI

Maximum likelihood weighted information (MLWI) and maximum posterior weighted information (MPWI)
KL

Kullback-Leibler (KL) and posterior Kullback-Leibler (KLP) values for item selection
Ii

Item information functions, first and second derivatives (dichotomous and polytomous models)
simulateRespondents

Simulation of multiple examinees of adaptive tests
testList

Testing the format of the input lists
Pi

Item response probabilities, first, second and third derivatives (dichotomous and polytomous models)
nextItem

Selection of the next item
EPV

Expected Posterior Variance (EPV)
genPolyMatrix

Item bank generation (polytomous models)
randomCAT

Random generation of adaptive tests (dichotomous and polytomous models)