Studied the performance of rank (percentile) estimators in a basic two-stage hierarchical model capturing essential features of more complicated models commonly used to estimate effects. Simulation results highlight the need to assess whether even optimal percentile estimators perform sufficiently well to be used to evaluate teachers or schools.…

Investigated the data demands associated with the marginal maximum likelihood (MML) expected a posterior (EAP) methodology and the precision of the resulting parameter estimates when data fit the underlying model through simulation. Also studied the extent to which a misspecified prior distribution would affect the item and person parameter…

Develops an item-parameter estimation procedure using an EM algorithm for the continuous-response model (F. Samejima, 1973). Examines the usefulness of this model using simulated data. Results show that the procedure performs well in estimating items and theta parameters. (SLD)

The benefits of item response theory (IRT) will only accrue to a testing program to the extent that model assumptions are met. Obtaining accurate item parameter estimates is a critical first step. However, the sample sizes required for stable parameter estimation are often difficult to obtain in practice, particularly for the more complex models.…

The robustness of the polytomous Item Response Theory (IRT) model to violations of the unidimensionality assumption was studied. A secondary purpose was to provide guidelines to practitioners to help in deciding whether to use an IRT model to analyze their data. In a simulation study, the unidimensionality assumption was deliberately violated by…

Studied whether ordered latent class models can be used as nonparametric item response theory (NIRT) models to scale polytomous models. Simulation findings show that the Bayesian estimation method presented can handle the inequality restrictions on the parameters and the sparseness of the data quite well. (SLD)

Studied the one-parameter Item Response Theory model with normal item-characteristic curves in a longitudinal context. Results of a simulation suggest that the proposed procedure is rather robust against departures from normality. However, the estimation of the correlations between regression parameters can be seriously biased. (SLD)

Proposes a model for constrained computerized adaptive testing in which the information in the test at the trait level (theta) estimate is maximized subject to the number of possible constraints on the content of the test. Test assembly relies on a linear-programming approach. Illustrates the approach through simulation with items from the Law…

Developed models to investigate the fit of parametric item response models by comparing them to models fitted under nonparametric assumptions. Illustrated these techniques through simulation studies and real-data examples. Discusses the identifiability and estimation consistency of item response theory models. (SLD)

A model for constrained computerized adaptive testing is proposed in which the information on the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum information at the current ability estimate fixing…

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)

Developed an item response model for characterizing test-compromise that enables the estimation of item preview and score-gain distributions. In the approach, models parameters and posterior distributions are estimated by Markov Chain Monte Carlo procedures. Simulation study results suggest that when at least some test items are known to be…

Robustness of the school-level item response theoretic (IRT) model to violations of distributional assumptions was studied in a computer simulation. In situations where school-level precision might be acceptable for real school comparisons, expected a posteriori estimates of school ability were robust over a range of violations and conditions.…

Using simulation, the effect that misspecification of elements in the weight matrix has on estimates of basic parameters of the linear logistic test model was studied. Results indicate that, because specifying elements of the weight matrix is a subjective process, it must be done with great care. (SLD)

Accuracy of item parameter estimates is a critical concern for any application of item response theory (IRT). However, the necessary sample sizes are often difficult to obtain in practice, particularly for the more complex models. A promising avenue of research concerns modified item response models. This study both replicates and improves on an…