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Quality of Life Research
Gepubliceerd in:

01-08-2007 | Original Paper

Differential item functioning and health assessment

Auteurs: Jeanne A. Teresi, John A. Fleishman

Gepubliceerd in: Quality of Life Research | bijlage 1/2007

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Abstract

Establishing measurement equivalence is important because inaccurate assessment may lead to incorrect estimates of effects in research, and to suboptimal decisions at the individual, clinical level. Examination of differential item functioning (DIF) is a method for studying measurement equivalence. An item (i.e., one question in a longer scale) exhibits DIF if the item response differs across groups (e.g., gender, race), controlling for an estimate of the construct being measured. A distinction between applications in health, as contrasted with other settings such as educational and aptitude testing, is that there are many health-related constructs and multiple measures of each, few of which have received much critical evaluation. Discussed in this article are several methods for detection of differential item functioning (DIF), including non-parametric and parametric methods such as logistic regression, and those based on item response theory. Basic definitions and criteria for DIF detection are provided, as are steps in performing the analyses. Recommendations are presented and future directions discussed.
vorige artikel The role of the bifactor model in resolving dimensionality issues in health outcomes measures
volgende artikel Evaluating measurement equivalence using the item response theory log-likelihood ratio (IRTLR) method to assess differential item functioning (DIF): applications (with illustrations) to measures of physical functioning ability and general distress
Literatuur
1.
Crane, P. K., Gibbons, L. E., Ocepek-Welikson, K., Cook, K., Cella, D., Narasimhalu, K., Hays, R., & Teresi, J. A comparison of two sets of criteria for determining the presence of differential item functioning using ordinal logistic regression. Quality of Life Research, this issue.
2.
Teresi, J. A., Ocepek-Welikson, K., Kleinman, M., Cook, K. F., Crane, P., Gibbons, L. E., Morales, L. S., Orlando-Edelen, M., & Cella, D. Evaluating measurement equivalence using the item response theory log-likelihood ratio (IRTLR) method to assess differential item functioning (DIF):Applications (with illustrations) to measures of physical functioning ability and general distress. Quality of Life Research, this issue.
3.
Camilli, G., & Shepard, L. A. (1994). Methods for identifying biased test items. Thousand Oaks, California: Sage Publications.
4.
Holland, P. W., & Wainer, H. (1993). Differential item functioning. Hillsdale, NJ: Lawrence Erlbaum.
5.
Millsap, R. E., & Everson, H. T. (1993). Methodology review: Statistical approaches for assessing measurement bias. Applied Psychological Measurement, 17, 297–334.CrossRef
6.
Potenza, M. T., & Dorans, N. J. (1995). DIF assessment for polytomously scored items: A framework for classification and evaluation. Applied Psychological Measurement, 19, 23–37.CrossRef
7.
Thissen, D., Steinberg, L., & Wainer, H. (1993). Detection of differential item functioning using the parameters of item response models. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 67–113). Hillsdale NJ: Lawrence Erlbaum, Inc.
8.
Teresi, J. A. (2001). Statistical methods for examination of differential item functioning (DIF) with applications to cross-cultural measurement of functional, physical and mental health. Journal of Mental Health and Aging, 7, 31–40.
9.
Teresi, J. A. (2006). Different approaches to differential item functioning in health applications: Advantages, disadvantages and some neglected topics. Medical Care, 44, S152–S170.PubMedCrossRef
10.
King, G., Murray, C. J. L., Salomon, J. A., & Tandon, A. (2004). Enhancing the validity and cross-cultural comparability of measurement in survey research. American Political Science Review, 98, 191–207.CrossRef
11.
Hambleton, R. K. (2006). Good practices for identifying differential item functioning. Medical Care, 44(Suppl 3), S182–S188.PubMedCrossRef
12.
Teresi, J. A., Kleinman, M., & Ocepek-Welikson, K. (2000). Modern psychometric methods for detection of differential item functioning: Application to cognitive assessment measures. Statistics in Medicine, 19, 1651–1683.PubMedCrossRef
13.
Fleishman, J. A., & Lawrence, W. F. (2003) Demographic variation in SF-12 scores: True differences or differential item functioning? Medical Care, 41(Suppl. 7), III75–III86.PubMed
14.
Fleishman, J. A., Spector, W. D., & Altman, B. M. (2002). Impact of differential item functioning on age and gender differences in functional disability. Journal of Gerontology: Social Sciences, 57B, S275–S284.
15.
Orlando-Edelen, M., Thissen, D., Teresi, J. A., Kleinman, M., & Ocepek-Welikson, K. (2006). Identification of differential item functioning using item response theory and the likelihood-based model comparison approach: Application to the Mini-mental status examination. Medical Care, 44, S134–S142.PubMedCrossRef
16.
Morales, L. S., Flowers, C., Gutiérrez, P., Kleinman, M., & Teresi, J. A. (2006). Item and scale differential functioning of the Mini-Mental Status Exam assessed using the DFIT methodology. Medical Care, 44, S143–S151.PubMedCrossRef
17.
Crane, P. K., Gibbons, L. E., Jolley, L., & van Belle, G. (2006). DIF analysis with ordinal logistic regression techniques: DIFDETECT. Medical Care, 44(Suppl3), S115–S123.PubMedCrossRef
18.
Mantel, N., & Haenszel, W. M. (1959). Statistical aspects of the analysis of data from retrospective studies of disease. Journal of the National Cancer Institute, 22, 719–748.PubMed
19.
Holland, P. W., & Thayer, D. T. (1988). Differential item performance and the Mantel-Haenszel procedure. In H. Wainer & J. I. Braun (Eds.), Test validity. Hillsdale, NJ: Lawrence Erlbaum.
20.
Dorans, N. J., & Kulick, E. (1986). Demonstrating the utility of the standardization approach to assessing unexpected differential item performance on the Scholastic Aptitude Test. Journal of Educational Measurement, 23, 355–368.CrossRef
21.
Shealy, R., & Stout, W. (1993). A model-based standardization approach that separates true bias/DIF from group ability differences and detects test bias/DTF as well as item bias/DIF. Psychometrika, 58, 159–194.CrossRef
22.
Dorans, N. J., & Kulick, E. (2006). Differential item functioning on the Mini-Mental State Examination: An application of Mantel-Haenszel and standardization procedures. Medical Care, 44(Suppl. 3), S107–S114.PubMedCrossRef
23.
Roussos, L. A., & Stout, W. F. (1996). Simulation studies of the effects of small sample size and studied item parameters on SIBTEST and Mantel-Haenszel type I error performance. Journal of Educational Measurement, 33, 215–230.CrossRef
24.
Swaminathan, H., & Rogers, H. J. (1990). Detecting differential item functioning using logistic regression procedures. Journal of Educational Measurement, 26, 361–370.CrossRef
25.
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, Canada: Directorate of Human Resources Research and Evaluation, Department of National Defense. Retrieved from http://​www.​educ.​ubc.​ca/​faculty/​zumbo/​DIF/​index.​html.
26.
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.PubMedCrossRef
27.
Jodoin, M. G., & Gierl, M. J. (2001). Evaluating type I error and power rates using an effect size measure with the logistic regression procedure for DIF detection. Applied Measurement in Education, 14, 329–349.CrossRef
28.
Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores. Reading Massachusetts: Addison-Wesley Publishing Co.
29.
Lord, F. M. (1980). Applications of item response theory to practical testing problems. Hillsdale New Jersey: Lawrence Erlbaum.
30.
Hambleton, R. K., Swaminathan, H, & Rogers, H. J. (1991). Fundamentals of item response theory. Newbury Park, California: Sage Publications, Inc.
31.
Thissen, D. (1991). MULTILOGTM User’s guide. Multiple, categorical item analysis and test scoring using Item response theory. Chicago: Scientific Software, Inc.
32.
Thissen, D. (2001). IRTLRDIF v2.0b; Software for the Computation of the Statistics Involved in Item Response Theory Likelihood-Ratio Tests for Differential Item Functioning. Available on Dave Thissen’s web page.
33.
Raju, N. S., van der Linden, W. J., & Fleer, P. F. (1995). IRT-based internal measures of differential functioning of items and tests. Applied Psychological Measurement, 19, 353–368.CrossRef
34.
Flowers, C. P., Oshima, T. C., & Raju, N. S. (1999). A description and demonstration of the polytomous DFIT framework. Applied Psychological Measurement, 23, 309–326.CrossRef
35.
Muthén, B. O. (2002). Beyond SEM: General latent variable modeling. Behaviormetrika, 29, 81–117.CrossRef
36.
Muthén, L. K., & Muthén, B. O. (2004). MPLUS Statistical Analysis with latent variables. Users guide. Los Angeles, California: Muthén and Muthén.
37.
Meredith, W. (1964). Notes on factorial invariance. Psychometricka, 29, 177–185.CrossRef
38.
Gregorich, S. E. (2006). Do self-report instruments allow meaningful comparisons across diverse population groups? Testing measurement invariance using the confirmatory factor analysis framework. Medical Care, 44(Suppl 3), S78–S94.PubMedCrossRef
39.
Jones, R. N., & Gallo, J. J. (2002). Education and sex differences in the Mini-Mental State Examination: Effects of differential item functioning. Journal of Gerontology: Psychological Sciences, 57B, P548–P558.
40.
Jones, R. N. (2006). Identification of measurement differences between English and Spanish language versions of the Mini-mental State Examination: Detecting differential item functioning using MIMIC modeling. Medical Care, 44(Suppl 3), S124–S133.PubMedCrossRef
41.
Krause, N. (2002). A comprehensive strategy for developing closed-ended survey items for use in studies of older adults. Journal of Gerontology B Psychological Sciences, 57B, S263–S274.
42.
Allalouf, A., Hambleton, R., & Sireci, S. (1999). Identifying the causes of translation DIF on verbal items. Journal of Educational Measurement, 36, 185–198.CrossRef
43.
Gierl, M. J., & Khaliq, S. N. (2001). Identifying sources of differential item and bundle functioning on translated achievement tests: A confirmatory analysis. Journal of Educational Measurement, 38, 164–187.CrossRef
44.
Roussos, L., & Stout, W. (1996). A multidimensionality-based DIF analysis paradigm. Applied Psychological Measurement, 20, 355–371.CrossRef
45.
Nápoles-Springer, A. M., Santoyo-Olsson, J., O’Brien, H., & Stewart, A. L. (2006). Using cognitive interviews to develop surveys in diverse populations. Medical Care, 44(Suppl 3), S21–S30.PubMedCrossRef
46.
McHorney, C. A. (2003). Ten recommendations for advancing patient-centered outcomes measurement for older persons. Annals of Internal Medicine, 139, 403–409.PubMed
47.
Bolt, D. M. (2002). A Monte Carlo comparison of parametric and nonparametric polytomous DIF detection methods. Applied Psychological Measurement, 15, 113–141.
48.
Wainer, H. (1993). Model-based standardized measurement of an item’s differential impact. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 123–135). Hillsdale NJ: Lawrence Erlbaum, Inc.
49.
Nandakumar R., & Roussos L. (in press) Evaluation of CATSIB procedure in pretest setting. Journal of Educational and Behavioral Statistics.
50.
Zwick, R., Thayer, D. T., & Wingersky, M. (1994). A simulation study of methods for assessing differential item functioning in computerized adaptive tests. Applied Psychological Measurement, 18, 121–140.CrossRef
51.
Teresi, J. A., Holmes, D., Ramirez, M., Gurland, B. J., & Lantigua, R. (2001). Performance of cognitive tests among different racial/ethnic groups: Findings of differential item functioning and possible item bias. Journal of Mental Health and Aging, 7, 79–89.
52.
Teresi, J., Cross, P., & Golden, R. (1989). Some applications of latent trait analysis to the measurement of ADL. Journal of Gerontology: Social Sciences, 44, S196–S204.
53.
Morales, L. S., Reise, S. P., & Hays, R. D. (2000). Evaluating the equivalence of health care ratings by whites and hispanics. Medical Care, 38, 517–527.PubMedCrossRef
54.
Orlando, M., & Marshall, G. N. (2002) Differential item functioning in a Spanish translation of the PTSD Checklist: Detection and evaluation of impact. Psychological Assessment, 14, 50–59.PubMedCrossRef
55.
National Research Council. (2004). Measuring racial discrimination. Panel on methods for assessing discrimination. Committee on National Statistics, Division of Behavioral and Social Sciences and Education. Washington DC: The National Academies Press.
56.
Johanson, G., & Alsmadi, A. (2002). Differential person functioning. Educational and Psychological Measurement, 62, 435–443.CrossRef
57.
Hunter, J. E., & Schmidt, F. L. (2000) Racial and gender bias in ability and achievement tests. Psychology, Public Policy and Law, 6, 151–158.CrossRef
Metagegevens
Titel
Differential item functioning and health assessment
Auteurs
Jeanne A. Teresi
John A. Fleishman
Publicatiedatum
01-08-2007
Uitgeverij
Springer Netherlands
Gepubliceerd in
Quality of Life Research / Uitgave bijlage 1/2007
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-007-9184-6

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