Classical automated test assembly (ATA) methods assume fixed and known coefficients for the constraints and the objective function. This hypothesis is not true for the estimates of item response theory parameters, which are crucial elements in test assembly classical models. To account for uncertainty in ATA, we propose a chance-constrained…

Calibration of new items online has been an important topic in item replenishment for multidimensional computerized adaptive testing (MCAT). Several online calibration methods have been proposed for MCAT, such as multidimensional "one expectation-maximization (EM) cycle" (M-OEM) and multidimensional "multiple EM cycles"…

Bayesian network models offer a large degree of flexibility for modeling dependence among observables (item outcome variables) from the same task, which may be dependent. This article explores four design patterns for modeling locally dependent observations: (a) no context--ignores dependence among observables; (b) compensatory context--introduces…

Proposed person-fit statistics that are designed for use in a computerized adaptive test (CAT) and derived critical values for these statistics using cumulative sum (CUSUM) procedures so that item-score patterns can be classified as fitting or misfitting. Compared nominal Type I errors with empirical Type I errors through simulation studies. (SLD)

Four statistics are proposed for the detection of local dependence (LD) among items analyzed using item response theory. Simulation results show that, under the locally dependent condition, the X-squared and G-squared indexes appear to be sensitive in detecting LD or multidimensionality among items. (SLD)

Some alternative criteria for item selection in adaptive testing are proposed that take into account uncertainty in the ability estimates. A simulation study shows that the likelihood weighted information criterion is a good alternative to the maximum information criterion. Another good alternative uses a Bayesian expected a posteriori estimator.…