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Differential Item Functioning (DIF) in composite health measurement scale: Recommendations for characterizing DIF with meaningful consequences within the Rasch model framework

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  • Alexandra Rouquette
  • Jean-Benoit Hardouin
  • Alexis Vanhaesebrouck
  • Véronique Sébille
  • Joël Coste

Abstract

Objective: The aims were to review practices concerning Differential Item Functioning (DIF) detection in composite measurement scales, particularly those used in health research, and to provide guidance on how to proceed if statistically significant DIF is detected. Methods: This work specifically addressed the Rasch model which is the subject of growing interest in the field of health owing to its particularly advantageous properties. There were three steps: 1) Literature review to describe current practices; 2) Simulation study to determine under which conditions encountered in health research studies can erroneous conclusions be drawn from group comparisons when a scale is affected by DIF but which is not considered; 3) Based on steps 1 and 2, formulation of recommendations that were subsequently reviewed by leading internationally recognized experts. Results: Four key recommendations were formulated to help researchers to determine whether statistically significant DIF is meaningful in practice, according to the kind of DIF (uniform or non-uniform) and the DIF effect size. Conclusion: This work provides the first recommendations on how to deal in practice with the presence of DIF in composite measurement scales used in health research studies.

Suggested Citation

  • Alexandra Rouquette & Jean-Benoit Hardouin & Alexis Vanhaesebrouck & Véronique Sébille & Joël Coste, 2019. "Differential Item Functioning (DIF) in composite health measurement scale: Recommendations for characterizing DIF with meaningful consequences within the Rasch model framework," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-16, April.
    • Handle: RePEc:plo:pone00:0215073
    DOI: 10.1371/journal.pone.0215073
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    References listed on IDEAS

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    1. Geoff Masters, 1982. "A rasch model for partial credit scoring," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 149-174, June.
    2. Jean-Benoit Hardouin, 2005. "SIMIRT: Stata module to process data generated by IRT models," Statistical Software Components S450402, Boston College Department of Economics, revised 16 May 2013.
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    1. Cathrine Nyhus Hagum & Shaher A. I. Shalfawi, 2020. "The Factorial Validity of the Norwegian Version of the Multicomponent Training Distress Scale (MTDS-N)," IJERPH, MDPI, vol. 17(20), pages 1-25, October.
    2. Jeanne A. Teresi & Chun Wang & Marjorie Kleinman & Richard N. Jones & David J. Weiss, 2021. "Differential Item Functioning Analyses of the Patient-Reported Outcomes Measurement Information System (PROMIS®) Measures: Methods, Challenges, Advances, and Future Directions," Psychometrika, Springer;The Psychometric Society, vol. 86(3), pages 674-711, September.

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