Estimating latent distributions |
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Authors: | Dr. Robert J. Mislevy |
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Affiliation: | (1) National Opinion Research Center, USA;(2) Educational Testing Service, 08540 Princeton, N.J. |
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Abstract: | Consider vectors of item responses obtained from a sample of subjects from a population in which ability is distributed with densityg(), where the are unknown parameters. Assuming the responses depend on 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.The author would like to thank R. Darrell Bock for his comments, suggestions, and encouragement during the course of this work. |
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Keywords: | latent distributions maximum likelihood EM algorithm empirical Bayes estimation Gaussian resolution beta-binomial model item response theory |
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