The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Estimating Latent Distributions
Abstract
Consider vectors of item responses obtained from a sample of subjects from a population in which ability θ is distributed with density g (θ‖α), where the α are unknown parameters. Assuming the responses depend on θ through a fully specified item response model, this paper presents maximum likelihood equations for the estimation of the population parameters directly from the observed responses; i.e., without estimating an ability parameter for each subject. Also provided are asymptotic standard errors and tests of fit, computing approximations, and details of four special cases: a non-parametric approximation, a normal solution, a resolution of normal components, and a beta-binomial solution.
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Citations
Cites
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
Statistical Theories of Mental Test Scores
Rozeboom, W. W., Lord, F. M., Novick, M. R., & Birnbaum, A. (1969) · American Educational Research Journal · doi:10.2307/1162101 · Cited by 8,022
Probabilistic Models for Some Intelligence and Attainment Tests
(1961) · Information and Control · doi:10.1016/s0019-9958(61)80061-2 · Cited by 6,939
The Advanced Theory of Statistics.
Clarke, G. M., Kendall, M., & Stuart, A. (1978) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344782 · Cited by 6,658
The American Journal of Human Genetics
S., J. (1950) · Population (French Edition) · doi:10.2307/1523704 · Cited by 5,028
Maximum likelihood estimation from incomplete data via the EM algorithm
Dempster, A. P. (1977) · Journal of the Royal Statistical Society Series A (Statistics in Society) · Cited by 4,543
Journal of the Royal Statistical Society.
(1923) · The Economic Journal · doi:10.1093/ej/33.130.269 · Cited by 3,219
Marginal Maximum Likelihood Estimation of Item Parameters: Application of an EM Algorithm
Bock, R. D., & Aitkin, M. (1981) · Psychometrika · doi:10.1007/bf02293801 · Cited by 2,339
Finding the Observed Information Matrix When Using the EM Algorithm
Louis, T. A. (1982) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1982.tb01203.x · Cited by 2,229
Probabilistic Models for some Intelligence and Attainment Tests.
Wolins, L., Wright, B. D., & Rasch, G. (1982) · Journal of the American Statistical Association · doi:10.2307/2287805 · Cited by 1,979
Cited by
Rose, M., Bjorner, J. B., Becker, J., Fries, J. F., & Ware, J. E. (2008) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2006.06.025 · Cited by 503
Randomization-Based Inference about Latent Variables from Complex Samples
Mislevy, R. J. (1991) · Psychometrika · doi:10.1007/bf02294457 · Cited by 477
Self-citationEstimating Population Characteristics From Sparse Matrix Samples of Item Responses
Mislevy, R. J., Beaton, A. E., Kaplan, B., & Sheehan, K. M. (1992) · Journal of Educational Measurement · doi:10.1111/j.1745-3984.1992.tb00371.x · Cited by 447
Self-citationBeyond group-mean differences: The concept of item bias.
Thissen, D., Steinberg, L., & Gerrard, M. (1986) · Psychological Bulletin · doi:10.1037//0033-2909.99.1.118 · Cited by 294
Lindsay, B., Clogg, C. C., & Grego, J. (1991) · Journal of the American Statistical Association · doi:10.1080/01621459.1991.10475008 · Cited by 289
Metadata
- Authors
- Mislevy, R. J.
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 1984-09
- Volume
- 49
- Issue
- 3
- Pages
- 359-381
- ISSN
- 0033-3123 (ISSN-L)
- 1860-0980
- OpenAlex
- W1973102368
- Cited by
- 338
- References
- 28
- FWCI
- 13.72
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
