The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
The Rasch Testlet Model
Abstract
The Rasch testlet model for both dichotomous and polytomous items in testlet-based tests is proposed. It can be viewed as a special case of the multidimensional random coefficients multinomial logit model (MRCMLM). Therefore, the estimation procedures for the MRCMLM can be directly applied. Simulations were conducted to examine parameter recovery under the dichotomous Rasch testlet model and the partial-credit testlet model. Results indicated that the item and person parameters as well as the random testlet effects could be recovered very accurately under all the simulated conditions. As sample sizes were increased, the root mean square errors of the estimates decreased to an acceptable level. An empirical example of an English test with 11 testlets was given. Index terms: multidimensional item response model, item bundle, marginal maximum likelihood estimation, parameter recovery.
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McCullagh, P., & Nelder, J. A. (1989) · doi:10.1007/978-1-4899-3242-6 · Cited by 16,836
Sampling-based approaches to calculating marginal densities
Gelfand, A. E., & Smith, A. F. M. (1990) · Journal of the American Statistical Association · doi:10.1080/01621459.1990.10476213 · Cited by 6,606
A Rasch model for partial credit scoring
Masters, G. N. (1982) · Psychometrika · doi:10.1007/bf02296272 · Cited by 3,782
Cited by
Leite, W. L., Svinicki, M., & Shi, Y. (2010) · Educational and Psychological Measurement · doi:10.1177/0013164409344507 · Cited by 448
Assessing elementary students’ computational thinking in everyday reasoning and robotics programming
Chen, G., Shen, J., Barth-Cohen, L., Jiang, S., Huang, X., & Eltoukhy, M. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.03.001 · Cited by 420
Measuring progressions: Assessment structures underlying a learning progression
Wilson, M. (2009) · Journal of Research in Science Teaching · doi:10.1002/tea.20318 · Cited by 329
Self-citationFull-Information Item Bifactor Analysis of Graded Response Data
Gibbons, R. D., Bock, R. D., Hedeker, D., Weiss, D. J., Segawa, E., Bhaumik, D. K., Kupfer, D. J., Frank, E., Grochocinski, V. J., & Stover, A. (2007) · Applied Psychological Measurement · doi:10.1177/0146621606289485 · Cited by 269
Metadata
- Authors
- Wang, W.-C., & Wilson, M.
- Venue
- Applied Psychological Measurement
- Publisher
- SAGE Publications
- Published
- 2005-03
- Volume
- 29
- Issue
- 2
- Pages
- 126-149
- ISSN
- 0146-6216 (ISSN-L)
- 1552-3497
- OpenAlex
- W2081967827
- Cited by
- 192
- References
- 3
- FWCI
- 5.23
- Type
- journal article
- Language
- en
- Open access
- closed
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