Bayes Modal Estimation in Item Response Models
- 1 June 1986
- journal article
- Published by Cambridge University Press (CUP) in Psychometrika
- Vol. 51 (2) , 177-195
- https://doi.org/10.1007/bf02293979
Abstract
This article describes a Bayesian framework for estimation in item response models, with two-stage prior distributions on both item and examinee populations. Strategies for point and interval estimation are discussed, and a general procedure based on the EM algorithm is presented. Details are given for implementation under one-, two-, and three-parameter binary logistic IRT models. Novel features include minimally restrictive assumptions about examinee distributions and the exploitation of dependence among item parameters in a population of interest. Improved estimation in a moderately small sample is demonstrated with simulated data.Keywords
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