Exact small-sample differential item functioning methods for polytomous items with illustration based on an attitude survey

Journal of Educational Measurement

Volumn 41, Issue 4, 2004, Pages 331-344

  Meyer, J Patrick ^a   Huynh, Huynh ^b,c   Seaman, Michael A ^b  

^a JAMES MADISON UNIVERSITY   (United States)

^b UNIVERSITY OF SOUTH CAROLINA   (United States)

^c Department of Education   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 11144335533     PISSN: 00220655     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1745-3984.2004.tb01169.x     Document Type: Review

References (28)

1. Agresti, A. (1996). An introduction to categorical data analysis. New York: Wiley.
2. American Educational Research Association/American Psychological Association/National Council in Measurement in Education. (1999). Standards for educational and psychological testing. Washington, DC: American Educational Research Association.
3. Clauser, B. E., & Mazor, K. (1998). Using statistical procedures to identify differentially functioning test items. Educational Measurement: Issues and Practice, 17, 31-44.
4. Cytel. (2000). StatXact 4 for Windows users manual. Cambridge, MA: Cytel Software Corporation.
5. Donoghue, J. R., & Alien, N. L. (1992). "Thin" versus "thick" matching in the Mantel-Haenszel procedure for detecting DIP. Research Report 92-76. Princeton, NJ: Educational Testing Service.
6. Dorans, N., Schmitt, A., & Bleistein, C. (1992). The standardization approach to assessing comprehensive differential item functioning. Journal of Educational Measurement, 29, 309-319.
7. 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: Lawrence Erlbaum Associates, Inc.
8. Huynh, H. (1994). On equivalence between a partial credit item and a set of independent Rasch binary items. Psychometrika, 59, 111-119.
9. Huynh, H. (1996). Decomposition of a Rasch partial credit item into independent binary and indecomposable trinary items. Psychometrika, 61, 31-39.
10. Johnson, N. L., & Kotz, S. (1992). Distributions in statistics: Discrete distributions (2nd ed., pp. 143-165). New York: Wiley.
11. Lehman, E. L. (1975). Nonparametrics: Statistical methods based on ranks. San Francisco, CA: Holden-Day.
12. Mantel, N. (1963). Chi-square tests with one degree of freedom; extensions of the MantelHaenszel procedure. Journal of the American Statistical Association, 58, 690-700.
13. Mantel, N., & Haenszel, W. (1959). Statistical aspects of the analysis of data from retrospective studies of disease. Journal of the National Cancer Institute, 22, 719-748.
14. Marascuilo, L. A., & McSweeney, M. (1977). Nonparametric and distribution-free methods for the social sciences. Monterey, CA: Brooks/Cole.
15. Mazor, K. M., Clauser, B. E., & Hambleton, R. K. (1992). The effect of sample size on the functioning of the Mantel-Haenszel statistic. Educational and Psychological Measurement, 52, 443-451.
16. Muraki, E. (1992). A generalized partial credit model: Applications of an EM algorithm. Applied Psychological Measurement, 16, 159-176.
17. Parshall, C. G., & Miller, T. R. (1995). Exact versus asymptotic Mantel-Haenszel DIP statistics: A comparison of performance under small-sample conditions. Journal of Educational Measurement, 32, 302-316.
18. Reckase, M. D. (1979). Unifactor latent trait models applied to multifactor tests: Results and implications. Journal of Educational Statistics, 4, 207-230.
19. Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York: Wiley.
20. Sandman, R. S. (1980). The mathematics attitude inventory: Instrument and user's manual. Journal of Research in Mathematics Education, 11, 148-149.
21. SAS. (1990). SAS/STAT user's guide: Basics. Cary, NC: SAS Institute Inc.
22. Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147-177.
23. Wilson, M. (1988). Detecting and interpreting local item dependence using a family of Rasch models. Applied Psychological Measurement, 12, 353-364.
24. Zhang, J. (2001). E-mail communication to Huynh Huynh, February 23. Columbia, SC: University of South Carolina.
25. Zwick, R., & Ercikan, K. (1989). Analysis of differential item functioning in the NAEP history assessment. Journal of Educational Measurement, 26, 55-66.
26. Zwick, R., & Thayer, D. T. (1996). Evaluating the magnitude of differential item functioning in polytomous items. Journal of Educational and Behavioral Statistics, 21, 187-201.
27. Zwick, R., Thayer, D. T., & Mazzeo, J. (1997a). Describing and categorizing DIP in polytomous items. Research Report 97-05. Princeton, NJ: Educational Testing Service.
28. Zwick, R., Thayer, D. T., & Mazzeo, J. (1997b). Descriptive and inferential procedures for assessing DIP in polytomous items. Applied Measurement in Education, 10, 321-344.