Abstract
Background
Several techniques have been developed to detect differential item functioning (DIF), including ordinal logistic regression (OLR). This study compared different criteria for determining whether items have DIF using OLR.
Objectives
To compare and contrast findings from three different sets of criteria for detecting DIF using OLR. General distress and physical functioning items were evaluated for DIF related to five covariates: age, marital status, gender, race, and Hispanic origin.
Research design
Cross-sectional study.
Subjects
1,714 patients with cancer or HIV/AIDS.
Measures
A total of 23 items addressing physical functioning and 15 items addressing general distress were selected from a pool of 154 items from four different health-related quality of life questionnaires.
Results
The three sets of criteria produced qualitatively and quantitatively different results. Criteria based on statistical significance alone detected DIF in almost all the items, while alternative criteria based on magnitude detected DIF in far fewer items. Accounting for DIF by using demographic-group specific item parameters had negligible effects on individual scores, except for race.
Conclusions
Specific criteria chosen to determine whether items have DIF have an impact on the findings. Criteria based entirely on statistical significance may detect small differences that are clinically negligible.
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References
Hahn, E. A., Holzner, B., Kemmler, G., Sperner-Unterweger, B., Hudgens, S. A., & Cella, D. (2005). Cross-cultural evaluation of health status using item response theory: FACT-B comparisons between Austrian and U.S. patients with breast cancer. Evaluation & The Health Professions, 28, 233–259.
Eremenco, S. L., Cella, D., & Arnold, B. J. (2005). A comprehensive method for the translation and cross-cultural validation of health status questionnaires. Evaluation & The Health Professions, 28, 212–232.
Martin, M., Blaisdell, B., Kwong, J. W., & Bjorner, J. B. (2004). The Short-Form Headache Impact Test (HIT-6) was psychometrically equivalent in nine languages. Journal of Clinical Epidemiology, 57, 1271–1278.
Roorda, L. D., Jones, C. A., Waltz, M., Lankhorst, G. J., Bouter, L. M., van der Eijken, J. W., Willems, W. J., Heyligers, I. C., Voaklander, D. C., Kelly, K. D., & Suarez-Almazor, M. E. (2004). Satisfactory cross cultural equivalence of the Dutch WOMAC in patients with hip osteoarthritis waiting for arthroplasty. Annals of the Rheumatic Diseases, 63, 36–42.
Ryall, N. H., Eyres, S. B., Neumann, V. C., Bhakta, B. B., & Tennant, A. (2003). Is the Rivermead Mobility Index appropriate to measure mobility in lower limb amputees? Disability and Rehabilitation, 25, 143–153.
Angoff, W. H. (1993). Perspectives on differential item functioning methodology. In P. W. Holland & H. Wainer (Eds.), Differential item functioning. Hillsdale, NJ: Erlbaum.
Camilli, G., & Shepard, L. A. (1994). Methods for identifying biased test items. Thousand Oaks: Sage.
Millsap, R. E., & Everson, H. T. (1993). Methodology review: Statistical approaches for assessing measurement bias. Applied Psychological Measurement, 17, 297–334.
Holland, P. W., & Wainer, H. (Eds.) (1993). Differential item functioning. Hillsdale, NJ: Erlbaum.
Crane, P. K., van Belle, G., & Larson, E. B. (2004). Test bias in a cognitive test: Differential item functioning in the CASI. Statistics in Medicine, 23, 241–256.
Swaminathan, H., & Rogers, H. J. (1990). Detecting differential item functioning using logistic regression procedures. Journal of Educational Measurement, 27, 361–370.
Zumbo, B. D. (1999). A handbook on the theory and methods of differential item 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.
Gelin, M. N., & Zumbo, B. D. (2003). Differential item functioning results may change depending on how an item is scored: An illustration with Center for Epidemiologic Studies Depression scale. Educational & Psychological Measurement, 63, 65–74.
Crane, P. K., Gibbons, L. E., Jolley, L., & van Belle, G. (2006). Differential item functioning analysis with ordinal logistic regression techniques: DIFdetect and difwithpar. Medical Care, 44, S115–S123.
Ganz, P. A., Schag, C. A., Lee, J. J., & Sim, M. S. (1992). The CARES: A generic measure of health-related quality of life for patients with cancer. Quality of Life Research, 1, 19–29.
Schag, C. A., Ganz, P. A., & Heinrich, R. L. (1991). Cancer Rehabilitation Evaluation System-short form (CARES-SF). A cancer specific rehabilitation and quality of life instrument. Cancer, 68, 1406–1413.
Aaronson, N. K., Ahmedzai, S., Bergman, B., Bullinger, M., Cull, A., Duez, N. J., Filiberti, A., Flechtner, H., Fleishman, S. B., & de Haes, J. C., et al. (1993). The European Organization for Research and Treatment of Cancer QLQ-C30: A quality-of-life instrument for use in international clinical trials in oncology. Journal of the National Cancer Institute, 85, 365–376.
Cella, D. F., Tulsky, D. S., Gray, G., Sarafian, B., Linn, E., Bonomi, A., Silberman, M., Yellen, S. B., Winicour, P., & Brannon, J., et al. (1993). The Functional Assessment of Cancer Therapy scale: Development and validation of the general measure. Journal of Clinical Oncology, 11, 570–579.
Cella, D. F., & Bonomi, A. E. (1995). Measuring quality of life: 1995 update. Oncology (Williston Park), 9, 47–60.
Hays, R. D., Sherbourne, C. D., & Mazel, R. M. (1993). The RAND 36-Item Health Survey 1.0. Health Economics, 2, 217–227.
McHorney, C. A., Ware, J. E. Jr., & Raczek, A. E. (1993). The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical Care, 31, 247–263.
Ware, J. E. Jr., & Sherbourne, C. D. (1992). The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Medical Care, 30, 473–483.
Hu, L.-T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3, 424–453.
Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.
Muraki, E., & Bock, D. (2003). PARSCALE for Windows. Chicago: SSI. Version 4.1.
Samejima, F. (1997). Graded response model. In W. J. van der Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory. NY: Springer.
Samejima F. (1969) Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph No. 17.
StataCorp. (2003). Stata statistical software: release 8.0. College Station, TX: StataCorp.
McCullagh P., & Nelder, J.A. (1989). Generalized linear models. London: Chapman and Hall.
Maldonado, G., & Greenland, S. (1993). Simulation study of confounder-selection strategies. American Journal of Epidemiology, 138, 923–936.
Crane, P. K., Hart, D. L., Gibbons, L. E., & Cook, K. F. (2006). A 37-item shoulder functional status item pool had negligible differential item functioning. Journal of Clinical Epidemiology, 59, 478–484.
Cella, D., Hahn, E. A., & Dineen, K. (2002). Meaningful change in cancer-specific quality of life scores: Differences between improvement and worsening. Quality of Life Research, 11, 207–221.
Eton, D. T., Cella, D., Yost, K. J., Yount, S. E., Peterman, A. H., Neuberg, D. S., Sledge, G. W., & Wood, W. C. (2004). A combination of distribution- and anchor-based approaches determined minimally important differences (MIDs) for four endpoints in a breast cancer scale. Journal of Clinical Epidemiology, 57, 898–910.
Crane, P. K., Gibbons, L. E., Narasimhalu, K., Lai, J. S., & Cella D. (2007). Rapid detection of differential item functioning in assessments of health-related quality of life: The Functional Assessment of Cancer Therapy. Quality of Life Research, 16, 101–114.
Long, J. S. (1997). Regression models for categorical and limited dependent variables. Advanced quantitative techniques in the social sciences. Thousand Oaks: Sage.
Shealy, R. T., & Stout, W. F. (1993). An item response theory model for test bias and differential test functioning. In P. W. Holland & H. Wainer (Eds.), Differential item functioning. Hillsdale, NJ: Erlbaum.
Acknowledgments
Some of these analyses were presented at the Advances in Health Outcomes Measurement: Exploring the Current State and the Future Applications of Item Response Theory, Item Banks, and Computerized-Adaptive Testing, June 24–25, 2004, in Bethesda, Maryland.
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Sources of support: Data collection was supported by grant R01 CA 60068 (Cella). Support for these analyses for Drs. Crane and Gibbons and Ms. Narasimhalu was provided by grant K08 AG 022232 from the National Institute on Aging (Crane). Dr. Gibbons was also supported by grant P50 AG 05136 from the National Institute on Aging (Murray Raskind). Dr. Teresi was supported by the Columbia University Resource Center for Minority Aging Research (AG 15294) and the Statistical Coordinating Center for the Patient Reported Outcomes Measurement Information System (PROMIS), NIH Roadmap Project (AR 052177). Dr. Hays was also supported by the UCLA/DREW Project EXPORT, National Institutes of Health, National Center on Health & Health Disparities (P20-MD00148-01), and the UCLA Center for Health Improvement in Minority Elders/Resource Centers for Minority Aging Research, National Institutes of Health, National Institute on Aging (AG-02-004).
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Crane, P.K., Gibbons, L.E., Ocepek-Welikson, K. et al. A comparison of three sets of criteria for determining the presence of differential item functioning using ordinal logistic regression. Qual Life Res 16 (Suppl 1), 69–84 (2007). https://doi.org/10.1007/s11136-007-9185-5
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DOI: https://doi.org/10.1007/s11136-007-9185-5