Random Generation of Response Patterns under Computerized Adaptive Testing with the R Package catR

Abstract

This paper outlines a computerized adaptive testing (CAT) framework and presents an R package for the simulation of response patterns under CAT procedures. This package, called catR, requires a bank of items, previously calibrated according to the four-parameter logistic (4PL) model or any simpler logistic model. The package proposes several methods to select the early test items, several methods for next item selection, different estimators of ability (maximum likelihood, Bayes modal, expected a posteriori, weighted likelihood), and three stopping rules (based on the test length, the precision of ability estimates or the classification of the examinee). After a short description of the different steps of a CAT process, the commands and options of the catR package are presented and practically illustrated.

Keywords

• computerized adaptive testing
• item selection
• ability estimation
• R package