Assessment of differential item functioning

Journal of Applied Measurement

Volumn 9, Issue 4, 2008, Pages 387-408

  Wang, Wen Chung ^a  

^a THE EDUCATION UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; HUMAN; PSYCHOLOGICAL MODEL; PSYCHOLOGY; STATISTICS;

HUMANS; MODELS, PSYCHOLOGICAL; PSYCHOLOGY;

EID: 58149193599     PISSN: 15297713     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (53)

1. Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43, 561-573.
2. Bolt, D. M. (2002). A Monte Carlo comparison of parametric and nonparametric polytomous DIF detection methods. Applied Measurement in Education, 15, 113-141.
3. Candell, G. L., and Drasgow, F. (1988). An iterative procedure for linking metrics and assessing item bias in item response theory. Applied Psychological Measurement, 12, 253-260.
4. Chang, H. H., Mazzeo, J., and Roussos, L. (1996). Detecting DIF for polytomously scored items: An adaptation of the SIBTEST procedure. Journal of Educational Measurement, 33, 333-353.
5. Clauser, B., Mazor, K., and Hambleton, R. K. (1993). The effects of purification of the matching criterion on the identification of DIF using the Mantel-Haenszel procedure. Applied Measurement in Education, 6, 269-279.
6. Cohen, A. S., Kim, S.-H., and Wollack, J. A. (1996). An investigation of the likelihood ratio test for detection of differential item functioning. Applied Psychological Measurement, 20, 15-26.
7. De Boeck, P., and Wilson, M. (Eds.) (2004). Explanatory item response models: A generalized linear and nonlinear approach. New York: Springer-Verlag.
8. Fischer, G. H. (1973). The linear logistic test model as an instrument in educational research. Acta Psychologica, 37, 359-374.
9. Hidalgo-Montesinos, M. D., and Gómez-Benito, J. (2003). Test purification and the evaluation of differential item functioning with multi-nominal logistic regression. European Journal of Psychological Assessment, 19, 1-11.
10. Holland, P. W., and Thayer, D. T. (1988). Differential item performance and the Mantel-Haenszel procedure. In H. Wainer and H. I. Braun (Eds.), Test validity (pp. 129-145). Hillsdale, NJ: Lawrence Erlbaum.
11. Holland, P. W., and Wainer, H. (Eds.) (1993). Differential item functioning. Hillsdale, NJ: Lawrence Erlbaum.
12. Kim, S.-H., and Cohen, A. S. (1998). Detection of differential item functioning under die graded response model with the likelihood ratio test. Applied Psychological Measurement, 22, 345-355.
13. Linacre, J. M. (1989). Many-facet Rasch measurement. Chicago: MESA Press.
14. Linacre, J. M. (2003). A user's guide to WINSTEPS: Rasch-model computer program [Computer program and manual]. Chicago: Winsteps.com.
15. Lord, F. M. (1980). Applications of item response theory to practical testing problems. Hillsdale, NJ: Lawrence Erlbaum.
16. Lunz, M. E., Wright, B. D., and Linacre, J. M. (1990). Measuring the impact of judge severity on examination scores. Applied Measurement in Education, 3, 331-345.
17. Luppescu, S. (1993). DIF detection examined. Rasch Measurement Transactions, 7(2), 285-286.
18. Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47, 149-174.
19. Myford, C. M., and Wolfe, E. W. (2003). Detecting and measuring rater effects using manyfacet Rasch measurement: Part I. Journal of Applied Measurement, 4, 386-422.
20. Myford, C. M., and Wolfe, E. W. (2004). Detecting and measuring rater effects using manyfacet Rasch measurement: Part II. Journal of Applied Measurement, 5, 189-227.
21. Navas-Ara, M. J., and Gómez-Benito, J. (2002). Effects of ability scale purification on identification of DIF. European Journal of Psychological Assessment, 18, 9-15
22. Rabe-Hesketh, S., Skrondal, A., and Pickles, A. (2003). Maximum likelihood estimation of generalized linear models with covariate measurement error. The Stata Journal, 3, 385-410.
23. Rabe-Hesketh, S., Skrondal, A., and Pickles, A. (2004). Generalized multilevel structural equation modeling. Psychometrika, 69, 167-190.
24. Raju, N. S., van der Linden, W. J., and Fleer, P. F. (1995). IRT-based internal measures of differential functioning of items and tests. Applied Psychological Measurement, 19, 353-368.
25. Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen, Denmark: Danish Institute for Educational Research. (Expanded edition, 1980. Chicago: University of Chicago Press.)
26. SAS Institute. (1999). The NLMIXED procedure [Computer program]. Cary, NC: Author.
27. Shealy, R., and Stout, W F. (1993). Amodel-based standardization approach that separates true bias/DIF from group differences and detects test bias/DIF as well as item bias/DIF. Psychometrika, 58, 159-194.
28. Sheu, C.-F., Chen, C.-T., Su, Y.-H., and Wang, W.-C. (2005). Using SAS PROC NLMIXED to fit item response theory models. Behavior Research Methods, 37, 202-218.
29. Skrondal, A., and Rabe-Hesketh, S. (2004). Generalized latent variable modeling: Multilevel, longitudinal and structural equation models. Boca Raton, FL: Chapman and Hall/CRC Press.
30. Smith, R. M. (1994). A comparison of the power of Rasch total and between-item fit statistics to detect measurement disturbances. Educational and Psychological Measurement, 54, 42-55.
31. Smith, R. M. (1996). A comparison of the Rasch separate calibration and between-fit methods of detecting item bias. Educational and Psychological Measurement, 56, 403-418.
32. Smith, R. M., and Suh, K. K. (2003). Rasch fit statistics as a test of the invariance of item parameter estimates. Journal of Applied Measurement, 4, 153-163.
33. Swaminathan, H., and Rogers, H. J. (1990). Detecting differential item functioning using logistic regression procedures. Journal of Educational Measurement, 27, 361-370.
34. Thissen, D., Steinberg, L., and Wainer, H. (1988). Use of item response theory in the study of group differences in trace lines. In H. Wainer and H. I. Braun (Eds.), Test validity (pp. 147-169). Hillsdale, NJ: Lawrence Erlbaum.
35. Waller, N. G. (1998). EZDIF: A program for the analysis of uniform and nonuniform differential item functioning. Applied Psychological Measurement, 22, 391.
36. Wang, W.-C. (2000a). Factorial modeling of differential distractor functioning in multiplechoice items. Journal of Applied Measurement, 1, 238-256.
37. Wang, W.-C. (2000b). Modeling effects of differential item functioning in polytomous items. Journal of Applied Measurement. 1, 63-82.
38. Wang, W.-C. (2000c). The simultaneous factorial analysis of differential item functioning. Methods of Psychological Research, 5(1), 56-76.
39. Wang, W.-C., (2004). Effects of anchor item methods on the detection of differential item functioning within the family of Rasch models. Journal of Experimental Education, 72, 221-261.
40. Wang, W.-C., and Chang, C. (1998). Rasch likelihood ratio test of differential item functioning. Chinese Journal of Psychology, 40, 15-32.
41. Wang, W.-C., Shih, C.-L., and Su, Y.-H. (2007). Establishing a common metric over groups for detection of differential item functioning. Paper submitted for publication.
42. Wang, W.-C., and Su, Y.-H. (2004a). Effects of average signed area between two item characteristic curves and test purification procedures on the DIF detection via the Mantel-Haenszel method. Applied Measurement in Education, 17, 113-144.
43. Wang, W.-C., and Su, Y.-H. (2004b). Factors influencing the Mantel and generalized Mantel-Haenszel methods for the assessment of differential item functioning in polytomous items. Applied Psychological Measurement, 28, 450-480.
44. Wang, W.-C., and Wilson, M. R. (2005a). Assessment of differential item functioning in testletbased items using the Rasch testlet model. Educational and Psychological Measurement, 65, 549-576.
45. Wang, W.-C., and Wilson, M. (2005b). The Rasch testlet model. Applied Psychological Measurement, 29, 126-149.
46. Wang, W.-C., and Yeh, Y.-L. (2003). Effects of anchor item methods on differential item functioning detection with the likelihood ratio test. Applied Psychological Measurement, 27, 479-498.
47. Welch, C., and Miller, T. (1995). Assessing differential item functioning in direct writing assessments: Problems and an example. Journal of Educational Measurement, 32, 163-178.
48. Wolfinger, R. D., and SAS Institute, (n.d.). Fitting nonlinear mixed models with the new NL-MIXED procedure. Retrieved June 16, 2007, from http://support.sas.com/rnd/app/papers/nlmixedsugi.pdf
49. Wright, B. D., and Stone, M. H. (1979). Best test design. Chicago: MESA Press.
50. Wright, B. D., and Masters, G. N. (1982). Rating scale analysis. Chicago: MESA Press.
51. Wright, B. D., Mead, R. J., and Draba, R. (1976). Detecting and correcting test item bias with a logistic response model (Research Memorandum 22). Chicago: MESA Statistical Laboratory, Department of Education, University of Chicago.
52. Wu, M., Adams, R. J., and Wilson, M. R. (1998). ACER ConQuest: Generalized item response modeling software [Computer program and manual]. Camberwell, VIC, Australia: Australian Council for Educational Research.
53. Zimowski, M. F., Muraki, E., Mislevy, R. J., and Bock, R. D. (1996). Bilog-MG: Multiplegroup IRT analysis and test maintenance for binary items [Computer program and manual]. Chicago: Scientific Software International.