Differential item and test functioning

Fritz Drasgow, Christopher D. Nye, Stephen Stark, Oleksandr S. Chernyshenko

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter focuses on differential item functioning (DIF) and differential test functioning (DTF) methods for dominance models, extending these approaches to ideal point models is an important area for future research. It describes effect size indices for DIF and DTF. In principle, the item response theory (IRT) approach to DIF and DTF should be preferred for discrete item responses, whether dichotomously scored or polytomously scored. The chapter also describes Thissen, Steinberg, and Wainer's likelihood ratio (LR) approach to the IRT study of DIF. Similar to the IRT methods for identifying DIF, the confirmatory factor analysis (CFA) approach relies on chi-square tests and empirically derived rules of thumb for identifying nonequivalence. The chapter presents an example of the study of DIF with IRT and CFA. An important consideration is that CFA is a dominance model: CFA assumes a linear relation between the latent trait and response variables.

Original languageEnglish (US)
Title of host publicationThe Wiley Handbook of Psychometric Testing
Subtitle of host publicationA Multidisciplinary Reference on Survey, Scale and Test Development
PublisherWiley-Blackwell
Pages885-899
Number of pages15
Volume2-2
ISBN (Electronic)9781118489772
ISBN (Print)9781118489833
DOIs
StatePublished - Jun 21 2017

Keywords

  • Chi-square tests
  • Confirmatory factor analysis
  • Differential item functioning
  • Differential test functioning
  • Effect size indices
  • Item response theory
  • Latent trait distribution
  • Likelihood ratio approach
  • Measurement equivalence
  • Response variables

ASJC Scopus subject areas

  • Social Sciences(all)

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