Generation of IRT Response Patterns under Computerized Adaptive Testing
Item membership assessment for a-stratified sampling
Breaking the item bank in item parameters and group membership (for co...
Checking whether the stopping rule is satisfied
EAP ability estimation (dichotomous and polytomous IRT models)
Standard error of EAP ability estimation (dichotomous and polytomous I...
Expected Posterior Variance (EPV)
Full distribution of ability estimator (dichotomous models only)
Global-discrimination index (GDI) and posterior global-discrimination ...
Item bank generation (dichotomous models)
Random generation of item response patterns under dichotomous and poly...
Item bank generation (polytomous models)
Item information functions, first and second derivatives (dichotomous ...
Numerical integration by linear interpolation (for catR internal use)
Function for weighted likelihood estimation (dichotomous a...
Kullback-Leibler (KL) and posterior Kullback-Leibler (KLP) values for ...
(Maximum) Expected Information (MEI)
Maximum likelihood weighted information (MLWI) and maximum posterior w...
Selection of the next item
Observed information function (dichotomous and polytomous models)
Item response probabilities, first, second and third derivatives (dich...
Random generation of adaptive tests (dichotomous and polytomous models...
Standard error of ability estimation (dichotomous and polytomous model...
Simulation of multiple examinees of adaptive tests
Selection of the first items
Testing the format of the list for content balancing under dichotomous...
Testing the format of the input lists
Ability estimation (dichotomous and polytomous models)
Provides routines for the generation of response patterns under unidimensional dichotomous and polytomous computerized adaptive testing (CAT) framework. It holds many standard functions to estimate ability, select the first item(s) to administer and optimally select the next item, as well as several stopping rules. Options to control for item exposure and content balancing are also available (Magis and Barrada (2017) <doi:10.18637/jss.v076.c01>).