This article extends the work by Armstrong and Shi on CUmulative SUM (CUSUM) person-fit methodology. The authors present new theoretical considerations concerning the use of CUSUM person-fit statistics based on likelihood ratios for the purpose of detecting cheating and random guessing by individual test takers. According to the Neyman-Pearson…

This book provides a general overview of computer based testing (CBT) and aims at an audience of practitioners and graduate students. The book discusses all aspects of BT without going into psychometric detail. This nontechnical and basic book is recommended as a textbook for students or new researchers. (SLD)

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)

Compared the nominal and empirical null distributions of the standardized log-likelihood statistic for polytomous items for paper-and-pencil (P&P) and computerized adaptive tests (CATs). Results show that the empirical distribution of the statistic differed from the assumed standard normal distribution for both P&P tests and CATs. Also…

Provides an overview of computerized adaptive testing (CAT) and introduces contributions to this special issue. CAT elements discussed include item selection, estimation of the latent trait, item exposure, measurement precision, and item-bank development. (SLD)

Two new methods have been proposed to determine unexpected sum scores on sub-tests (testlets) both for paper-and-pencil tests and computer adaptive tests. A method based on a conservative bound using the hypergeometric distribution, denoted p, was compared with a method where the probability for each score combination was calculated using a…