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Robustness of Person-Fit Decisions in Computerized Adaptive Testing (CT-04-06) ![]() Rob R. Meijer, University of Twente, Enschede, The Netherlands Executive Summary Several statistics have been recommended by researchers for identifying test taker responses to test items that are different from what would be expected, given what is known about the characteristics of the items and the estimated ability level of the test taker. Several of these statistics, often called person-fit statistics, are used for evaluating test taker responses to an entire string of items simultaneously. These statistics allow us to conclude that a particular item response theory (IRT) model either does or does not fit a person’s set of responses to items. (Note that IRT is a mathematical model used to analyze test data.) In this sense, these statistics are for use in a global method that only allows us to identify misfitting responses; that is, they do not help us to identify the type of behavior that caused the misfit.
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