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Testing for Differential Item Functioning Under the D-Scoring Method.

Dimiter M Dimitrov1,2, Dimitar V Atanasov3

  • 1George Mason University, Fairfax, VA, USA.

Educational and Psychological Measurement
|January 7, 2022
PubMed
Summary
This summary is machine-generated.

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The P-Z method efficiently tests for differential item functioning (DIF) using the D-scoring method (DSM). This approach simplifies DIF testing by comparing Z-scale normal deviates, proving effective for both item and test functioning.

Area of Science:

  • Psychometrics
  • Educational Measurement
  • Statistical Analysis

Background:

  • Differential Item Functioning (DIF) is crucial for unbiased measurement.
  • Existing methods may lack efficiency or applicability in certain frameworks.
  • The D-scoring method (DSM) offers a novel measurement framework.

Purpose of the Study:

  • To introduce and evaluate the P-Z method for DIF testing within the DSM framework.
  • To assess the statistical efficiency and power of the P-Z method.
  • To extend the P-Z method's applicability to differential test functioning.

Main Methods:

  • The P-Z method transforms item response probabilities (estimated via DSM) into Z-scale normal deviates.
  • DIF testing is reduced to comparing variances and means of these Z-deviates between reference and focal groups.
Keywords:
D-scoring methoddifferential item functioningtest bias

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  • A simulation study was conducted to evaluate method performance.

    • Main Results:

    • The P-Z method demonstrated high efficiency, characterized by low Type I error rates and high statistical power.
    • The simulation results support the effectiveness of the P-Z method.
    • The P-Z method is directly applicable for detecting differential test functioning.

    Conclusions:

    • The P-Z method provides an efficient and robust approach to DIF testing within the DSM framework.
    • The method is suitable for both item-level and test-level DIF analysis.
    • Recommendations for practical implementation and future research, including Item Response Theory (IRT) applications, are discussed.