@article {354, title = {An item response model for characterizing test compromise}, journal = {Journal of Educational and Behavioral Statistics}, volume = {27}, number = {2}, year = {2002}, note = {References .American Educational Research Assn, US}, pages = {163-179}, abstract = {This article presents an item response model for characterizing test-compromise that enables the estimation of item-preview and score-gain distributions observed in on-demand high-stakes testing programs. Model parameters and posterior distributions are estimated by Markov Chain Monte Carlo (MCMC) procedures. Results of a simulation study suggest that when at least some of the items taken by a small sample of test takers are known to be secure (uncompromised), the procedure can provide useful summaries of test-compromise and its impact on test scores. The article includes discussions of operational use of the proposed procedure, possible model violations and extensions, and application to computerized adaptive testing. }, keywords = {computerized adaptive testing}, author = {Segall, D. O.} }