Detecting Person Misfit in Adaptive Testing Using Statistical Process Control Techniques

Krimpen-Stoop, Edith M. L. A. van; Meijer, Rob R.

doi:10.1007/0-306-47531-6_11

Cited by 41 publications

(60 citation statements)

References 17 publications

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“…This is not only the case for polytomously scored CATs and P&P tests but also for dichotomously scored tests (see e.g., van Krimpen-Stoop & Meijer, 1999c, 1999b.…”

Section: Discussionmentioning

confidence: 99%

“…Thus for these statistics a theoretical distribution can be used to determine the critical values. Van Krimpen-Stoop & Meijer (1999a) found that the use of theoretically determined critical values resulted in empirical Type I errors that were close to the nominal ones. …”

Section: Cumulative Sum Proceduresmentioning

confidence: 95%

“…Recently, some studies investigated the assessment of person fit in CATs with dichotomously scored items (e.g., Nering, 1997;van Krimpen-Stoop & Meijer, 1999b, 1999c. However, there are no studies known to the authors that deal with personfit research in a CAT with polytomously scored items.…”

Section: Detection Of Person Misfit In Computerized Adaptive Tests Wimentioning

confidence: 99%

“…Both van Krimpen-Stoop & Meijer (1999b) and Bradlow, Weiss, & Cho (1998) proposed to use statistical process control techniques to detect person misfit in a CAT Van Krimpen-Stoop & Meijer (1999b) proposed statistics to be used in a CUSUM procedure to investigate person fit in an on-line application or after complete administration of a CAT with dichotomously scored items. These statistics were based on the responses to single items resulting in a sample size of 1 at each t. Because the theoretical distribution of these statistics is a Bernoulli distribution, and not a standard normal distribution, it was necessary to determine critical values to classify a score pattern as nonfitting by means of a simulation study.…”

Section: Cumulative Sum Proceduresmentioning

confidence: 99%

“…One dataset was simulated in which 1, 000 9s were drawn from N (0; 1). The simulation procedure was analogous to the procedure for dichotomously scored items in van Krimpen-Stoop & Meijer (1999c).…”

Section: Pandp Testsmentioning

confidence: 99%

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Detection of Person Misfit in Computerized Adaptive Tests with Polytomous Items

Krimpen-Stoop¹,

Meijer

2002

Applied Psychological Measurement

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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 person misfit with polytomous items has hardly been explored. In this simulation study, the theoretical and empirical null distributions of a person-fit statistic for polytomous items are compared for P&P tests and CATs. Results show that the empirical distribution of this statistic was close to the standard normal distribution, for both P&P tests and CATs. Also statistics that are especially designed for a CAT are proposed. In these statistics observed and expected item scales are compared using cumulative sum (CUSUM) procedures.

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“…This is not only the case for polytomously scored CATs and P&P tests but also for dichotomously scored tests (see e.g., van Krimpen-Stoop & Meijer, 1999c, 1999b.…”

Section: Discussionmentioning

confidence: 99%

Section: Cumulative Sum Proceduresmentioning

confidence: 95%

Section: Detection Of Person Misfit In Computerized Adaptive Tests Wimentioning

confidence: 99%

Section: Cumulative Sum Proceduresmentioning

confidence: 99%

Section: Pandp Testsmentioning

confidence: 99%

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Detection of Person Misfit in Computerized Adaptive Tests with Polytomous Items

Krimpen-Stoop¹,

Meijer

2002

Applied Psychological Measurement

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Person Misfit

Meijer¹

2005

Encyclopedia of Statistics in Behavioral Science

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Methods are discussed that can be used to investigate the fit of an item score pattern to a test model. Person‐fit statistics that are formulated in the context of item response theory(IRT) take a prominent place in the literature. Also, methods formulated outside the IRT context, and methods investigating particular types of response behavior are discussed. Finally, the usefulness of person‐fit statistics to solve practical measurement problems is considered.

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Testing and Measurement

Hambleton

Pitoniak

2002

Stevens' Handbook of Experimental Psychology

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This chapter addresses many of the changes that are taking place in the educational and psychological measurement field today. First, different types of educational and psychological tests are described, and examples are provided of the variety of venues in which they are administered. Next, some major changes that have taken place in the field of psychometrics in the past 30 years are introduced; most prominent among them is the shift from classical test theory to item response theory (IRT). Following a comparison of classical test theory to IRT, and a discussion of the former's shortcomings, main IRT concepts and several widely used IRT models are presented in more detail. IRT model applications to test development and computer‐adaptive testing are described. An introduction to different types of computer‐based testing that vary along the adaptive continuum is also provided. Next, a number of other prominent changes that are taking place in the testing field that have methodological implications for the practice of measurement—new item types, cognitive‐based models for assessment, setting standards on tests, new conceptions of validity, and testing of candidates with disabilities—are outlined.

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Detecting Person Misfit in Adaptive Testing Using Statistical Process Control Techniques

Cited by 41 publications

References 17 publications

Detection of Person Misfit in Computerized Adaptive Tests with Polytomous Items

Detection of Person Misfit in Computerized Adaptive Tests with Polytomous Items

Person Misfit

Testing and Measurement

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