Generation of IRT Response Patterns under Computerized Adaptive Testing

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Documentation for package ‘catR’ version 3.17

• DESCRIPTION file.
• Package NEWS.

Help Pages

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)