Exploring new methods to detect person misfit in CAT

R.R. Meijer, Edith van Krimpen-Stoop

Research output: Book/ReportReportOther research output

Abstract

Item scores that do not fit an assumed item response theory model may cause the latent trait value to be inaccurately estimated. Several person-fit statistics for detecting nonfitting response behavior for paper-and-pencil tests have been proposed. In the context of computerized adaptive testing, the use of person-fit analysis is hardly explored. Because it has been shown that the distribution of existing person-fit statistics is not applicable in a computer adaptive test (CAT), new person-fit statistics are proposed, and critical values for these statistics are derived from existing statistical theory. The theoretical and empirical distributions are compared, and a power study is performed.
Original languageUndefined
Place of PublicationNewton, PA, USA
PublisherLaw School Admission Council
Number of pages13
Publication statusPublished - Sep 2006

Publication series

NameLSAC research report series
PublisherLaw School Admission Council
No.99-13

Keywords

  • IR-104263

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