Previous work on the effects of dimensionality on parameter estimation for dichotomous models is extended to the graded response model. Datasets are generated that differ in the number of latent factors as well as their interdimensional association, number of test items, and sample size. (SLD)

Previous work on the effects of dimensionality on parameter estimation was extended from dichotomous models to the polytomous graded response (GR) model. A multidimensional GR model was developed to generate data in one-, two-, and three-dimensions, with two- and three-dimensional conditions varying in their interdimensional associations. Test…

One important and promising application of item response theory (IRT) is computerized adaptive testing (CAT). The implementation of a nominal response model-based CAT (NRCAT) was studied. Item pool characteristics for the NRCAT as well as the comparative performance of the NRCAT and a CAT based on the three-parameter logistic (3PL) model were…

Effects of dimensionality on ability estimation of an adaptive test were examined using generated data in Bayesian computerized adaptive testing (CAT) simulations. Generally, increasing interdimensional difficulty association produced a slight decrease in test length and an increase in accuracy of ability estimation as assessed by root mean square…