Showed how Taylor approximation can be used to generate a linear approximation to a logistic item characteristic curve and a linear ability estimator. Demonstrated how, for a specific simulation, this could result in the special case of a Robbins-Monro item selection procedure for adaptive testing. (SLD)

Proposes a mixture item response model for investigating individual differences in the selection of response categories in multiple choice items. A real data example illustrates how the model can be used to distinguish examinees disproportionately attracted to different types of distractors, and a simulation study evaluates item parameter recovery…

A selection model for meta-analysis is proposed that models the selection process and corrects for the consequences of selection by publication on estimates of the mean and variance of the effect parameters. Simulation studies show that the model substantially reduces bias when the model specification is correct. (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.…

Considers an approach to validating the selection of education indicators by incorporating them into a multilevel structural model and using the estimates from that model in policy-relevant simulations. The potential of this approach is demonstrated with data from the National Education Longitudinal Study of 1988. (SLD)