TitleAn item response model for characterizing test compromise
Publication TypeJournal Article
Year of Publication2002
AuthorsSegall, DO
JournalJournal of Educational and Behavioral Statistics
Publication Languageeng
Keywordscomputerized adaptive testing

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.