Nonparametric and group-based person-fit statistics : a validity study and an empirical example

R.R. Meijer

Research output: Book/ReportReportProfessional

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In person-fit analysis, the object is to investigate whether an item score pattern is improbable given the item score patterns of the other persons in the group or given what is expected on the basis of a test model. In this study, several existing group-based statistics to detect such improbable score patterns were investigated, along with the cut scores that have been proposed in the literature to classify an item score pattern as aberrant. Through a simulation study and an empirical study, the power of three person-fit statistics was compared, and the practical use of various cut scores was investigated. The empirical study involved 437 Dutch sophomores studying psychology and pedagogics taking an examination on test theory. It was also demonstrated that person-fit statistics can be used to detect persons with a deficiency of knowledge on an achievement test. While one of the statistics was less appropriate in the simulation, the power of the three approaches was approximately the same in the empirical example.
Original languageEnglish
Place of PublicationEnschede
PublisherUniversity of Twente, Faculty Educational Science and Technology
Number of pages38
Publication statusPublished - 1994

Publication series

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


  • Research Methodology
  • Achievement Tests
  • Test Items
  • Cutting Scores
  • Group Membership
  • Higher Education
  • Foreign Countries
  • Identification
  • Simulation
  • Validity
  • Knowledge Level
  • Nonparametric Statistics
  • METIS-140148
  • IR-104202
  • Classification
  • College Students
  • Power (Statistics)


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