Expected a posteriori has a number of advantages over maximum likelihood estimation or maximum a posteriori (MAP) estimation methods. These include ability estimates (thetas) for all response patterns, less regression towards the mean than MAP ability estimates, and a lower average squared error. R. D. Bock and R. J. Mislevy (1982) state that the…

A polychotomous nominal response model-based computerized adaptive test (CAT) was simulated using data from 1,093 University of Texas students. The ability estimation of this model and its overall performance were compared with those of a dichotomous three-parameter logistic model-based CAT. Advantages and drawbacks of nominal response CAT are…

This study extended item parameter recovery studies in item response theory to the nominal response model (NRM). The NRM may be used with computerized adaptive testing, testlets, demographic items, and items whose alternatives provide educational diagnostic information. Moreover, with the increasing popularity of performance-based assessment, the…

Computerized adaptive testing procedures (CATPs) based on the graded response method (GRM) of F. Samejima (1969) and the partial credit model (PCM) of G. Masters (1982) were developed and compared. Both programs used maximum likelihood estimation of ability, and item selection was conducted on the basis of information. Two simulated data sets, one…

The effect of dimensionality on an adaptive test's ability estimation was examined. Two-dimensional data sets, which differed from one another in the interdimensional ability association, the correlation among the difficulty parameters, and whether the item discriminations were or were not confounded with item difficulty, were generated for 1,600…

F. M. Lord's flexilevel, computerized adaptive testing (CAT) procedure was compared to an item-response theory-based CAT procedure that uses Bayesian ability estimation with various standard errors of estimates used for terminating the test. Ability estimates of flexilevel CATs were as accurate as were those of Bayesian CATs. (TJH)

A study involving 1,000 simulated examinees compared the partial credit and graded response models in computerized adaptive testing (CAT). The graded response model fit the data well and provided slightly more accurate ability estimates than those of the partial credit model. Benefits of polytomous model-based CATs are discussed. (SLD)

A computerized adaptive test (CAT) based on the nominal response model (NR CAT) was implemented, and the performance of the NR CAT and a CAT based on the three-parameter logistic model was compared. The NR CAT produced trait estimates comparable to those of the three-parameter test. (SLD)

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…

The robustness of a partial credit (PC) model-based computerized adaptive test's (CAT's) ability estimation to items that did not fit the PC model was investigated. A CAT program was written based on the PC model. The program used maximum likelihood estimation of ability. Item selection was on the basis of information. The simulation terminated…

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…

To date, the majority of computerized adaptive testing (CAT) systems for achievement and aptitude testing have been based on the dichotomous item response models. However, current research with polychotomous model-based CATs is yielding promising results. This study extends previous work on nominal response model-based CAT (NR CAT) and compares…