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How Item Residual Heterogeneity Affects Tests for Differential Item Functioning.

Carol M Woods1, Jared Harpole1

  • 1University of Kansas, Lawrence, USA.

Applied Psychological Measurement
|June 9, 2018
PubMed
Summary

Differential item functioning (DIF) testing methods can be unreliable when item residual homogeneity is violated. The Mantel-Haenszel (MH) test demonstrated robustness to this heterogeneity, unlike logistic regression and item response theory (IRT).

Keywords:
DIFdifferential item functioningheterogeneitylogistic regression

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Area of Science:

  • Psychometrics
  • Educational Measurement
  • Statistical Modeling

Background:

  • Differential item functioning (DIF) is crucial for fair assessment, identifying items that function differently across groups.
  • Popular DIF detection methods often assume item residual homogeneity, an assumption rarely discussed in research.
  • Violations of this assumption, known as item residual heterogeneity, can impact the validity of DIF findings.

Purpose of the Study:

  • To investigate the impact of item residual heterogeneity on common DIF detection methods.
  • To propose and illustrate a strategy for detecting item residual heterogeneity.
  • To evaluate the performance of binary logistic regression, two-group item response theory (IRT), and the Mantel-Haenszel (MH) test under conditions of heterogeneity.

Main Methods:

  • Explanation of the item residual homogeneity assumption in DIF testing.
  • Development and empirical illustration of a method to detect item residual heterogeneity.
  • Monte Carlo simulations to assess the Type I error rates and power of DIF methods with varying degrees of heterogeneity.

Main Results:

  • Binary logistic regression showed inflated Type I error and reduced power when item residual heterogeneity was present.
  • Two-group item response theory (IRT) exhibited attenuated power and biased estimates of latent group means and standard deviations.
  • The Mantel-Haenszel (MH) test proved robust to item residual heterogeneity, likely due to its non-reliance on the logistic function.

Conclusions:

  • Item residual heterogeneity poses a significant threat to the accuracy of logistic regression and IRT-based DIF detection.
  • The Mantel-Haenszel (MH) test is a more reliable method for DIF analysis when item residual homogeneity cannot be assumed.
  • Researchers should consider assessing item residual homogeneity to ensure the validity of DIF analyses.