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Bayesian Estimation in the Three-Parameter Logistic Model

Hariharan Swaminathan · Janice A. Gifford

104 citations0/0 files storedPsychometrika

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Psychometric Methodologies and Testing Statistical Distribution Estimation and Applications Statistical Methods and Bayesian Inference

Abstract

A joint Bayesian estimation procedure for the estimation of parameters in the three-parameter logistic model is developed in this paper. Procedures for specifying prior beliefs for the parameters are given. It is shown through simulation studies that the Bayesian procedure (i) ensures that the estimates stay in the parameter space, and (ii) produces better estimates than the joint maximum likelihood procedure as judged by such criteria as mean squared differences between estimates and true values.

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References

2012Applications of Item Response Theory To Practical Testing Problems 1981Marginal Maximum Likelihood Estimation of Item Parameters: Application of an EM Algorithm 1986Bayes Modal Estimation in Item Response Models 1954Statistical methods in educational and psychological research.1980VERTICAL EQUATING USING THE RASCH MODEL 1985Bayesian Estimation in the Two-Parameter Logistic Model 1982Bayesian Estimation in the Rasch Model

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