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Differential item functioning analysis with ordinal logistic regression techniques. DIFdetect and difwithpar.

Paul K Crane1, Laura E Gibbons, Lance Jolley

  • 1Department of Internal Medicine, University of Washington, Seattle, Washington, USA. pcrane@u.washington.edu

Medical Care
|October 25, 2006
PubMed
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This study introduces an ordinal logistic regression model to detect differential item functioning (DIF) in the Mini-Mental State Examination (MMSE). The model identified several MMSE items with significant DIF related to language, suggesting a need for careful item selection.

Area of Science:

  • Psychometrics
  • Educational Measurement
  • Cognitive Assessment

Background:

  • Differential Item Functioning (DIF) is crucial for ensuring test fairness.
  • The Mini-Mental State Examination (MMSE) is widely used but may contain items with DIF.
  • Existing DIF detection methods can be complex and require further investigation.

Purpose of the Study:

  • To present and apply an ordinal logistic regression model for DIF identification.
  • To investigate DIF in the MMSE related to various demographic and administrative factors.
  • To evaluate the utility of combining ordinal logistic regression with Item Response Theory (IRT) for DIF detection.

Main Methods:

  • Ordinal logistic regression models were developed to detect nonuniform and uniform DIF.

Related Experiment Videos

  • Item Response Theory (IRT) ability estimation was integrated into the models.
  • DIF was examined across multiple covariates including language, race, ethnicity, age, education, and sex.

    • Main Results:

    • Five MMSE items exhibited DIF related to the language of test administration.
    • These language-related DIF items also showed DIF associated with other covariates.
    • The proposed model demonstrated effectiveness in identifying DIF.

    Conclusions:

    • Ordinal logistic regression combined with IRT provides a viable approach for DIF detection.
    • Several MMSE items demonstrate significant DIF, particularly concerning language.
    • Further research should focus on the criteria for determining DIF, not solely the detection technique.