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Egberink, Iris J. L.; Meijer, Rob R.; Tendeiro, Jorge N. – Educational and Psychological Measurement, 2015
A popular method to assess measurement invariance of a particular item is based on likelihood ratio tests with all other items as anchor items. The results of this method are often only reported in terms of statistical significance, and researchers proposed different methods to empirically select anchor items. It is unclear, however, how many…
Descriptors: Personality Measures, Computer Assisted Testing, Measurement, Test Items
Tendeiro, Jorge N.; Meijer, Rob R. – Applied Psychological Measurement, 2012
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…
Descriptors: Cheating, Individual Testing, Adaptive Testing, Statistics

van Krimpen-Stoop, Edith M. L. A.; Meijer, Rob R. – Applied Psychological Measurement, 2002
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…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Response Theory, Statistical Distributions

Meijer, Rob R.; Nering, Michael L. – Applied Psychological Measurement, 1999
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)
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Selection
van Krimpen-Stoop, Edith M. L. A.; Meijer, Rob R. – 2000
Item scores that do not fit an assumed item response theory model may cause the latent trait value to be estimated inaccurately. For computerized adaptive tests (CAT) with dichotomous items, several person-fit statistics for detecting nonfitting item score patterns have been proposed. Both for paper-and-pencil (P&P) test and CATs, detection of…
Descriptors: Adaptive Testing, Computer Assisted Testing, Goodness of Fit, Item Response Theory