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Please use this identifier to cite or link to this item: http://hdl.handle.net/11299/114468

Title: The use of prior distributions in marginalized Bayesian item parameter estimation: A didactic
Authors: Harwell, Michael R.
Baker, Frank B.
Issue Date: 1991
Citation: Harwell, Michael R & Baker, Frank B. (1991). The use of prior distributions in marginalized Bayesian item parameter estimation: A didactic. Applied Psychological Measurement, 15, 375-389. doi:10.1177/014662169101500409
Abstract: The marginal maximum likelihood estimation (MMLE) procedure (Bock & Lieberman, 1970; Bock & Aitkin, 1981) has led to advances in the estimation of item parameters in item response theory. Mislevy (1986) extended this approach by employing the hierarchical Bayesian estimation model of Lindley and Smith (1972). Mislevy’s procedure posits prior probability distributions for both ability and item parameters, and is implemented in the PC-BILOG computer program. This paper extends the work of Harwell, Baker, and Zwarts (1988), who provided the mathematical and implementation details of MMLE in an earlier didactic paper, by encompassing Mislevy’s marginalized Bayesian estimation of item parameters. The purpose was to communicate the essential conceptual and mathematical details of Mislevy’s procedure to practitioners and to users of PC-BILOG, thus making it more accessible. Index terms: Bayesian estimation, BILOG, item parameter estimation, item response theory.
URI: http://purl.umn.edu/114468
Appears in Collections:Volume 15, 1991

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