Synonyms
Definition
Differential item functioning refers to the situation where members from different groups (age, gender, race, education, culture) on the same level of the latent trait (disease severity, quality of life) have a different probability of giving a certain response to a particular item.
Description
Differential item functioning (DIF) is a threat to the validity of a patient-reported outcome (PRO) instrument. DIF occurs when subjects on the same level of the latent trait, such as disease severity, answer differently to the same item depending on their group memberships (e.g., age group, gender, race) (Chang, 2005; Holland & Thayer, 1988). The validity of the instrument is threatened because the response to the DIF item is governed by something other than the construct that the instrument is intended to measure. For example, crying spells is one of the symptoms for patients with depression, but this concept is reported more by...
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References
Angoff, W. H. (1984). Scales, norms, and equivalent scores. Princeton, NJ: Educational Testing Service.
Angoff, W. H., & Ford, S. F. (1973). Item-race interaction on a test of scholastic aptitude. Journal of Educational Measurement, 10, 95–105.
Berk, R. A. (Ed.). (1982). Handbook of methods for detecting test bias. Baltimore: John Hopkins University Press.
Chang, C. H. (2005). Item response theory and beyond: Advanced in patient-reported outcomes measurement. In W. R. Lenderking & D. A. Revicki (Eds.), Advancing health outcomes research methods and clinical applications (pp. 37–55). McLean, VA: Degnon Associated.
Chang, H., Mazzeo, J., & Roussos, R. (1996). Detect DIF for polytomously scored items: An adaptation of Shealy-Stout’s SIBTEST procedure. Journal of Educational Measurement, 33, 333–353.
Fidalgo, A. M., & Madeira, J. M. (2008). Generalized Mantel-Haenszel methods for differential item function detection. Educational and Psychological Measurement, 68(6), 940–958.
Finch, H. (2005). The MIMIC model as a method for detecting DIF: Comparison with Mantel-Haenszel, SIBTEST, and the IRT likelihood ratio. Applied Psychological Measurement, 29(4), 278–295.
Hambleton, R. K., & Swaninathan, H. (1985). Item response theory: Principles and applications. Hingham, MA: Kluwer.
Holland, P. W., & Thayer, D. T. (1988). Differential item performance and the Mantel-Haenszel procedure. In H. Wainer & H. I. Braun (Eds.), Test validity (pp. 129–145). Hillsdale, NJ: LEA.
Ironson, G. H. (1982). Use of chi-square and latent trait approaches for detecting item bias. In R. A. Berk (Ed.), Handbook of methods for detecting test bias (pp. 117–160). Baltimore: John Hopkins University Press.
Li, H.-H., & Stout, W. (1996). A new procedure for detection of crossing DIF. Psychometrika, 61, 647–677.
Linn, R. L., Levine, M. V., Hastings, C. N., & Wardrop, J. L. (1981). An investigation of item bias in a test of reading comprehension. Applied Psychological Measurement, 5, 159–173.
Mellenbergh, G. J. (1982). Contingency table models for assessing item bias. Journal of Educational Statistics, 7(2), 105–118.
Muthen, B., & Lehman, J. (1985). Multiple group IRT modeling: Application to item bias analysis. Journal of Educational Statistics, 10, 133–142.
Runder, L. M. (1977, April). An approach to biased item identification using latent trait measurement theory. Paper presented at the annual meeting of the American Educational Research Association, New York.
Scheuneman, J. D. (1979). A new method of assessing bias in test items. Journal of Educational Measurement, 16, 143–152.
Shealy, R., & Stout, W. (1993a). An item response theory model for test bias and differential test functioning. In P. Holland & H. Wainer (Eds.), Differential item functioning (pp. 197–240). Hillsdale, NJ: Earlbaum.
Shealy, R., & Stout, W. (1993b). A model-based standardization approach that separates true bias/DIF from group ability differences and detects test bias/DIF as well as item bias/DTF. Psychometrika, 58, 159–194.
Teresi, J. A., Ocepek-Welikson, K., Kleinman, M., Eimicke, J. P., Crane, P. K., Jones, R. N., et al. (2009). Analysis of differential item functioning in the depression item bank from the Patient Reported Outcome Measurement Information System (PROMIS): An item response theory approach. Psychology Science Quarterly, 51(2), 148–180.
Thissen, D., Steinberg, L., & Gerrard, M. (1986). Beyond group mean differences: The concept of item bias. Psychological Bulletin, 99, 118–128.
Thissen, D., Steinberg, L., & Wainer, H. (1988). Use of item response theory in the study of group differences in the trace lines. In H. Wainer & H. I. Braun (Eds.), Test validity (pp. 147–168). Hillsdale, NJ: LEA.
Zumbo, B. D. (1999). Functioning (DIF): Logistic regression modeling as a unitary framework for binary and Likert-type (ordinal) item scores. Ottawa, ON: Directorate of Human Resources Research and Evaluation, Department of National Defense.
Zwick, R., Donoghue, J. R., & Grima, A. (1993). Assessment of differential item functioning for performance tasks. Journal of Educational Measurement, 30, 233–251.
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Chen, WH., Revicki, D. (2014). Differential Item Functioning (DIF). In: Michalos, A.C. (eds) Encyclopedia of Quality of Life and Well-Being Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0753-5_728
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DOI: https://doi.org/10.1007/978-94-007-0753-5_728
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