The Nominal Response Model in Computerized Adaptive Testing

Abstract

Although most computerized adaptive tests (CATS) use dichotomous item response theory (IRT) models, research on the use of polytomous IRT models in CAT has shown promising results. This study implemented a CAT based on the nominal response model (NR CAT). Item pool requirements for the NR CAT were examined. The performance of the NR CAT and a CAT based on the three-parameter logistic (3PL) model was compared. For two-, three-, and four-category items, items with maximum information of at least.16 produced reasonably accurate trait estimation for tests with a minimum test length of approximately 15 to 20 items. The NR CAT was able to produce trait estimates comparable to those of the 3PL CAT. Implications of these results are discussed