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Generalized Mantel-Haenszel Estimators for Simultaneous Differential Item Functioning Tests.

Ivy Liu1, Thomas Suesse2, Samuel Harvey1

  • 1Victoria University of Wellington, New Zealand.

Educational and Psychological Measurement
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Summary
This summary is machine-generated.

This study introduces a generalized Mantel-Haenszel estimator to detect differential item functioning (DIF) in dependent items, avoiding the local independence assumption. The new method enables simultaneous DIF assessment for multiple items.

Keywords:
Mantel–Haenszel estimatordifferential item functioningdually consistentmultiple items

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Area of Science:

  • Psychometrics
  • Statistical modeling
  • Educational measurement

Background:

  • Differential item functioning (DIF) is crucial for test fairness.
  • The Mantel-Haenszel estimator is a popular DIF detection method.
  • Item Response Theory (IRT) relies on the local item independence assumption, often violated with item dependency.

Purpose of the Study:

  • To generalize the Mantel-Haenszel estimator for dependent items.
  • To develop a hypothesis test for simultaneous DIF assessment.
  • To evaluate the performance of the proposed DIF tests.

Main Methods:

  • Generalization of the Mantel-Haenszel estimator incorporating covariance of odds ratio estimators.
  • Development of a hypothesis testing framework for DIF in dependent items.
  • Simulation studies to assess test performance.

Main Results:

  • The generalized estimator accounts for item dependency.
  • The proposed hypothesis test effectively assesses simultaneous DIF.
  • Simulation results demonstrate the performance of the new DIF tests.

Conclusions:

  • The generalized Mantel-Haenszel method offers a viable alternative to IRT for DIF analysis with dependent items.
  • The new hypothesis test provides a robust approach for detecting DIF in multiple items concurrently.
  • The method is applicable to real-world datasets.