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Generalizing Beyond the Test: Permutation-Based Profile Analysis for Explaining DIF Using Item Features

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Listed:
  • Maria Bolsinova
  • Jesper Tijmstra

    (Tilburg University)

  • Leslie Rutkowski
  • David Rutkowski

    (Indiana University Centre for Educational Measurement)

Abstract

Profile analysis is one of the main tools for studying whether differential item functioning can be related to specific features of test items. While relevant, profile analysis in its current form has two restrictions that limit its usefulness in practice: It assumes that all test items have equal discrimination parameters, and it does not test whether conclusions about the item-feature effects generalize outside of the considered set of items. This article addresses both of these limitations, by generalizing profile analysis to work under the two-parameter logistic model and by proposing a permutation test that allows for generalizable conclusions about item-feature effects. The developed methods are evaluated in a simulation study and illustrated using Programme for International Student Assessment 2015 Science data.

Suggested Citation

  • Maria Bolsinova & Jesper Tijmstra & Leslie Rutkowski & David Rutkowski, 2024. "Generalizing Beyond the Test: Permutation-Based Profile Analysis for Explaining DIF Using Item Features," Journal of Educational and Behavioral Statistics, , vol. 49(2), pages 207-240, April.
    • Handle: RePEc:sae:jedbes:v:49:y:2024:i:2:p:207-240
    DOI: 10.3102/10769986231174927
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    References listed on IDEAS

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