Detection of person misfit in computerized adaptive tests with polytomous items

Edith van Krimpen-Stoop, R.R. Meijer

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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. Results show that the critical values of the CUSUM were symmetric around zero and similar across latent trait values. Moreover, the results show that for the CUSUM procedure fixed critical values for all examinees can be used.
Original languageEnglish
Place of PublicationEnschede
PublisherUniversity of Twente, Faculty Educational Science and Technology
Number of pages26
Publication statusPublished - 2000

Publication series

NameOMD research report
PublisherUniversity of Twente, Faculty of Educational Science and Technology


  • Adaptive Testing
  • Computer Assisted Testing
  • Goodness of Fit
  • METIS-136397
  • Scores
  • Test Items
  • IR-103773
  • Item Response Theory


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