A bifactor multidimensional item response theory model for differential item functioning analysis on testlet-based items

Applied Psychological Measurement

Volumn 35, Issue 8, 2011, Pages 604-622

  Fukuhara, Hirotaka ^a   Kamata, Akihito ^b  

^a University of Oregon ^*  (United States)

^b UNIVERSITY OF OREGON   (United States)

Author keywords

differential item functioning; MCMC; MIRT; testlets

Indexed keywords

EID: 84855176427     PISSN: 01466216     EISSN: 15523497     Source Type: Journal    
DOI: 10.1177/0146621611428447     Document Type: Article

References (32)

1. Albert J. H.Bayesian estimation of normal ogive item response curves using Gibbs sampling.Journal of Educational Statistics. 1992;17:251-269.
2. Befumi J.,Gelman A.,Park D. K.,Kaplan N.Practical issues in implementing and understanding Bayesian ideal point estimation.Political Analysis. 2005;13:171-187.
3. Bock R. D.,Gibbons R.,Schilling S. G.,Muraki E.,Wilson D. T.,Wood R.TESTFACT 4.0. Lincolnwood, IL: Scientific Software International; 2003:.
4. Bradlow E. T.,Wainer H.,Wang X.A Bayesian random effects model for testlets.Psychometrika. 1999;64:153-168.
5. Cai L.A two-tier full-information item factor analysis model with applications.Psychometrika. 2010;75:581-612.
6. Cai L.,Yang J.,Hansen M.Generalized full-information item bi-factor analysis.Psychological Methods. 2011;16:221-248.
7. DeMars C. E.Application of the bi-factor multidimensional item response theory model to testlet-based tests.Journal of Educational Measurement. 2006;43:145-168.
8. Dorans, N. J., & Holland, P. W. (1993). DIF detection and description: Mantel-Haenszel and standardization. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 35-66). Hillsdale, NJ: Erlbaum.
9. Douglas J. A.,Roussos L. A.,Stout W.Item-bundle DIF hypothesis testing: Identifying suspect bundles and assessing their differential functioning.Journal of Educational Measurement. 1996;33:465-484.
10. Finch H.The MIMIC model as a method for detecting DIF: Comparison with Mantel-Haenszel, SIBTEST, and the IRT likelihood ratio.Applied Psychological Measurement. 2005;29:278-295.
11. FukuharaH. (2009). A differential item functioning model for testlet-based items using a bi-factor multidimensional item response theory model: A Bayesian approach (Unpublished doctoral dissertation). Florida State University, Tallahassee.
12. Fukuhara H.,Kamata A.DIF detection in a presence of locally dependent items. Paper presented at the annual meeting of the Florida Educational Research Association; 2007 Tampa.
13. Gelman A.,Carlin J. B.,Stern H. S.,Rubin D. B.Bayesian data analysis. 2004). Bayesian data analysis (2nd ed.). Boca Raton, FL: Chapman & Hall/CRC.Boca Raton, FL: Chapman & Hall/CRC; 2004:.
14. Gibbons R. D.,Bock R. D.,Hedecker D.,Weiss D. J.,Segawa E.,Bhaumik D. K., Stover A.Full-information item bifactor analysis of graded response data.Applied Psychological Measurement. 2007;31:4-19.
15. Gibbons R. D.,Hedecker D.Full-information item bi-factor analysis.Psychometrika. 1992;57:423-436.
16. Kim S.An evaluation of a Markov chain Monte Carlo method for Rasch model.Applied Psychological Measurement. 2001;25:163-176.
17. Li Y.,Bolt D. M.,Fu J.A comparison of alternative models for testlets.Applied Psychological Measurement. 2006;30:3-21.
18. Lunn D. J.,Thomas A.,Best N.,Spiegelhalter D.WinBUGS-A Bayesian modelling framework: Concepts, structure, and extensibility.Statistics and Computing. 2000;10:325-337.
19. Monahan P. O.,McHorney C. A.,Stump T. E.,Perkins A. J.Odds ratio, Delta, ETS classification, and standardization measures of DIF magnitude for binary logistic regression.Journal of Educational and Behavioral Statistics. 2007;32:92-109.
20. Rijmen F.Efficient full information maximum likelihood estimation for multidimensional IRT models. Princeton, NJ: Educational Testing Service; 2009:.
21. Shealy R. T.,Stout W. F.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. 1993;58:159-194.
22. Sinharay S.Experiences with Markov chain Monte Carlo convergence assessment in two psychometric examples.Journal of Educational and Behavioral Statistics. 2004;29:461-488.
23. Thissen D.,Steinberg L.,Mooney J. A.Trace lines for testlets: A use of multiple-categorical-response models.Journal of Educational Measurement. 1989;26:247-260.
24. Wainer, H., Bradlow, E. T., & Du, Z. (2000). Testlet response theory: Analog for the 3-PL useful in testletbased adaptive testing. In W. J. van der Linden & C. A. W. Glas (Eds.), Computerized adaptive testing: Theory and practice (pp. 245-270). Boston, MA: Kluwer-Nijhoff.
25. Wainer H.,Bradlow E. T.,Wang X.Testlet response theory and its applications. New York, NY: Cambridge University Press; 2007:.
26. Wainer H.,Kiely G. L.Item clusters and computerized adaptive testing: A case for testlets.Journal of Educational Measurement. 1987;28:237-247.
27. Wang W.,Wilson M.Assessment of differential item functioning in testlet-based items using the Rasch testlet model.Educational and Psychological Measurement. 2005a;65:549-576.
28. Wang W.,Wilson M.The Rasch testlet model.Applied Psychological Measurement. 2005b;29:126-149.
29. Wang W. C.Effects of anchor item methods on the detection of differential item functioning within the family of Rasch models.Journal of Experimental Education. 2004;73:221-261.
30. Wang X.,Bradlow E. T.,Wainer H.A general Bayesian model for testlets: Theory and application.Applied Psychological Measurement. 2002;26:109-128.
31. Wang X.,Bradlow E. T.,Wainer H.,Muller E. S.A Bayesian method for studying DIF: A cautionary tale filled with surprises and delights.Journal of Educational and Behavioral Statistics. 2008;22:363-384.
32. Yen W. M.Scaling performance assessment: Strategies for managing local item dependence.Journal of Educational Measurement. 1993;30:187-213.