Bayesian Estimation of Normal Ogive Item Response Curves Using Gibbs Sampling

James H. Albert

Journal of Educational and Behavioral Statistics, 1992, vol. 17, issue 3, 251-269

Abstract: The problem of estimating item parameters from a two-parameter normal ogive model is considered. Gibbs sampling (Gelfand & Smith, 1990) is used to simulate draws from the joint posterior distribution of the ability and item parameters. This method gives marginal posterior density estimates for any parameter of interest; these density estimates can be used to judge the accuracy of normal approximations based on maximum likelihood estimates. This simulation technique is illustrated using data from a mathematics placement exam.

Keywords: density estimates; EM algorithm; simulation (search for similar items in EconPapers)
Date: 1992
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:17:y:1992:i:3:p:251-269

DOI: 10.3102/10769986017003251

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