Generation of IRT Response Patterns under Computerized Adaptive Testing


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Documentation for package ‘catR’ version 3.16

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aStratified Item membership assessment for a-stratified sampling
breakBank Breaking the item bank in item parameters and group membership (for content balancing)
cat_pav Items parameters of the CAT_PAV data set (with item names)
checkStopRule Checking whether the stopping rule is satisfied
eapEst EAP ability estimation (dichotomous and polytomous IRT models)
eapSem Standard error of EAP ability estimation (dichotomous and polytomous IRT models)
EPV Expected Posterior Variance (EPV)
fullDist Full distribution of ability estimator (dichotomous models only)
GDI Global-discrimination index (GDI) and posterior global-discrimination index (GDIP) for item selection
genDichoMatrix Item bank generation (dichotomous models)
genPattern Random generation of item response patterns under dichotomous and polytomous IRT models
genPolyMatrix Item bank generation (polytomous models)
Ii Item information functions, first and second derivatives (dichotomous and polytomous models)
integrate.catR Numerical integration by linear interpolation (for catR internal use)
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
MEI (Maximum) Expected Information (MEI)
MWI Maximum likelihood weighted information (MLWI) and maximum posterior weighted information (MPWI)
nextItem Selection of the next item
OIi Observed information function (dichotomous and polytomous models)
Pi Item response probabilities, first, second and third derivatives (dichotomous and polytomous models)
plot.cat Random generation of adaptive tests (dichotomous and polytomous models)
plot.catResult Simulation of multiple examinees of adaptive tests
print.cat Random generation of adaptive tests (dichotomous and polytomous models)
print.catResult Simulation of multiple examinees of adaptive tests
randomCAT Random generation of adaptive tests (dichotomous and polytomous models)
semTheta Standard error of ability estimation (dichotomous and polytomous models)
simulateRespondents Simulation of multiple examinees of adaptive tests
startItems Selection of the first items
tcals Items parameters of the TCALS 1998 data set and subgroups of items
test.cbList Testing the format of the list for content balancing under dichotomous or polytomous IRT models
testList Testing the format of the input lists
thetaEst Ability estimation (dichotomous and polytomous models)