Multidimensional componential item response theory models for polytomous items

Applied Psychological Measurement

Volumn 25, Issue 1, 2001, Pages 19-37

  Hoskens, Machteld ^a   De Boeck, Paul ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0035530479     PISSN: 01466216     EISSN: None     Source Type: Journal    
DOI: 10.1177/01466216010251002     Document Type: Article

References (48)

1. Ackerman, T. A., & Spray, J. A. (1986). A general model for item dependency (ACT Research Report 87-9). Iowa City IA: ACT.
2. Adams, R. J., Wilson, M., & Wang, W. (1997). The multidimensional random coefficients multinomial logit model. Applied Psychological Measurement, 21, 1-23.
3. Akaike, H. (1977). On entropy maximization principle. In P. R. Krishnaiah (Ed.), Applications of statistics (pp. 27-41). Amsterdam: North Holland.
4. Andrich, D. (1985). A latent-trait model for items with response dependencies: Implications for test construction and analysis. In S. E. Embretson (Ed.), Test design: Developments in psychology and psychometrics (pp. 245-275). New York: Academic Press.
5. Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee's ability. In F. M. Lord & M. R. Novick (Eds.), Statistical theories of mental test scores (pp. 397-472). Reading MA: Addison-Wesley.
6. Bishop, Y. M. M., Fienberg, S. E., & Holland, P. W. (1975). Discrete multivariate analysis. Cambridge MA: MIT Press.
7. Bock, R. D. (1972). Estimating item parameters and latent ability when responses are scored in two or more nominal categories. Psychometrika, 37, 29-51.
8. Bock, R. D., & Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm. Psychometrika, 46, 443-459.
9. Chen, W., & Thissen, D. (1997). Local dependence indexes for item pairs using item response theory. Journal of Educational and Behavioral Statistics, 22, 265-289.
10. Deming, W. E., & Stephan, F. F. (1940). On a least squares adjustment of a sampled frequency table when the expected marginal totals are known. Annals of Mathematical Statistics, 11, 427-444.
11. Embretson (Whitely), S. E. (1980). Multicomponent latent trait models for ability tests. Psychometrika, 45, 479-494.
12. Embretson, S. E. (1984). A general latent trait model for response processes. Psychometrika, 49, 175-186.
13. Embretson, S. E. (1995). A measurement model for linking individual learning to processes and knowledge: Application to mathematical reasoning. Journal of Educational Measurement, 32, 277-294.
14. Fischer, G. H. (1973a). Ein Beitrag zum Speed-Power Problem [A contribution to the speed-power problem]. In G. Reinert (Ed.), Bericht ueber den 27. Kongress der Deutschen Gesellschaft fuer Psychologie in Kiel 1970 . Goettingen, Germany: Verlag fuer Psychologie.
15. Fischer, G. H. (1973b). The linear logistic test model as an instrument in educational research. Acta Psychologica, 37, 359-374.
16. Fischer, G. H. (1995). The linear logistic test model. In G. H. Fischer & I. W. Molenaar (Eds.), Rasch models: Foundations, recent developments, and applications (pp. 131-155). New York: Springer-Verlag.
17. Fischer, G. H., & Formann, A. K. (1982). Some applications of logistic latent trait models with linear constraints on the parameters. Applied Psychological Measurement, 6, 397-416.
18. Geerts, G., & Heestermans, H. (Red.). (1984). Van Dale Groot woordenboek der Nederlandse taal [Van Dale extensive dictionary of the Dutch language] (11de uitgave). Utrecht/Antwerpen, The Netherlands: Van Dale Lexicografie.
19. Hoskens, M., & De Boeck, P. (1995). Componential IRT models for polytomous items. Journal of Educational Measurement, 32, 364-384.
20. Hoskens, M., & De Boeck, P. (1997). A parametric model for local dependence among test items. Psychological Methods, 2, 261-277.
21. Jannarone, R. J. (1986). Conjunctive item response theory kernels. Psychometrika, 51, 357-373.
22. Janssen, R. (1994). Psychometric modeling of componentially designed synonym tasks. Unpublished Dissertation, University of Leuven, Belgium.
23. Janssen, R., & De Boeck, P. (1997). Psychometric modeling of componentially designed synonym tasks. Applied Psychological Measurement, 21, 37-50.
24. Kelderman, H. (1996). Multidimensional Rasch models for partial-credit scoring. Applied Psychological Measurement, 20, 155-168.
25. Kelderman, H., & Rijkes, C. P. M. (1994). Loglinear multidimensional IRT models for polytomously scored items. Psychometrika, 59, 149-176.
26. Kelderman, H., & Steen, R. (1993). LOGIMO [Computer program]. Groningen, The Netherlands: ProGAMMA.
27. Maris, E. (1995). Psychometric latent response models. Psychometrika, 60, 523-547.
28. Mislevy, R. J., & Verhelst, N. (1990). Modeling item responses when different subjects employ different solution strategies. Psychometrika, 55, 195-215.
29. Mislevy, R. J., & Wilson, M. (1996). Marginal maximum likelihood estimation for a psychometric model of discontinuous development. Psychometrika, 61, 41-71.
30. Patz, R. (1996). Markov chain Monte Carlo methods for item response theory models with applications for the National Assessment of Educational Progress (Doctoral Dissertation, Carnegie-Mellon University, Pittsburgh, 1997). Dissertation Abstracts International, 57/11, 7030.
31. Rosenbaum, P. R. (1988). Item bundles. Psychometrika, 53, 349-359.
32. Spada, H., & McGaw, B. (1985). The assessment of learning effects with linear logistic test models. In S. E. Embretson (Ed.), Test design: Developments in psychology and psychometrics (pp. 169-194). New York: Academic Press.
33. Steinberg, L., & Thissen, D. (1996). Uses of item response theory and the testlet concept in the measurement of psychopathology. Psychological Methods, 1, 81-97.
34. Sternberg, R. J. (1977). Intelligence, information processing, and analogical reasoning: The componential analysis of human intelligence. Hillsdale NJ: Erlbaum.
35. Sternberg, R. J. (1985). Beyond IQ: A triarchic theory of human intelligence. New York: Cambridge University Press.
36. Thissen, D., & Steinberg, L. (1986). A taxonomy of item response models. Psychometrika, 51, 567-577.
37. Thissen, D., & Steinberg, L. (1988). Data analysis using item response theory. Psychological Bulletin, 104, 385-395.
38. Thissen, D., Steinberg, L., & Mooney, J. A. (1989). Trace lines for testlets: A use of multiple-categorical-response: models. Journal of Educational Measurement, 26, 247-260.
39. Verhelst, N. D., & Glas, C. A. (1993). A dynamic generalization of the Rasch model. Psychometrika, 58, 395-415.
40. Wainer, H., & Kiely, G. L. (1987). Item clusters and computerized adaptive testing: A case for testlets. Journal of Educational Measurement, 24, 185-201.
41. Wilson, M. (1988). Detecting and interpreting local item dependence using a family of Rasch models. Applied Psychological Measurement, 12, 353-364.
42. Wilson, M. (1989). Saltus: A psychometric model of discontinuity in cognitive development. Psychological Bulletin, 105, 276-289.
43. Wilson, M., & Adams, R. J. (1995). Rasch models for item bundles. Psychometrika, 60, 181-198.
44. Wu, M. L. (1997). The development and application of a fit test for use with marginal maximum likelihood estimation and generalised item response models. Unpublished Master's Dissertation, University of Melbourne, Australia.
45. Wu, M. L., Adams, R., & Wilson, M. (1997). CONQUEST [Computer program]. Melbourne, Australia: Australian Council for Educational Research.
46. Yamamoto, K., & Gitomer, D. H. (1993). Application of a HYBRID model to a test of cognitive skill representation. In N. Frederiksen, R. J. Mislevy, & I.I. Bejar (Eds.), Test theory for a new generation of tests. (pp. 275-295). Hillsdale NJ: Erlbaum.
47. Yen, W. M. (1984). Effects of local item dependence on the fit and equating performance of the three-parameter logistic model. Applied Psychological Measurement, 8, 125-145.
48. Yen, W. M. (1993). Scaling performance assessments: Strategies for managing local item dependence. Journal of Educational Measurement, 30, 187-213.