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Bayesian Estimation in the Two-Parameter Logistic Model

Published online by Cambridge University Press:  01 January 2025

Hariharan Swaminathan and
Janice A. Gifford
Hariharan Swaminathan*
Affiliation:
University of Massachusetts, Amherst
Janice A. Gifford
Affiliation:
Mount Holyoke College
*
Requests for reprints should be sent to H, Swaminathan, School of Education, University of Massachusetts, Amherst, MA 01003.
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Abstract

A Bayesian procedure is developed for the estimation of parameters in the two-parameter logistic item response model. Joint modal estimates of the parameters are obtained and procedures for the specification of prior information are described. Through simulation studies it is shown that Bayesian estimates of the parameters are superior to maximum likelihood estimates in the sense that they are (a) more meaningful since they do not drift out of range, and (b) more accurate in that they result in smaller mean squared differences between estimates and true values.

Keywords

Bayesian estimatesitem response modeltwo-parameter logistic modelmodal estimatesmaximum likelihood estimates

Information

Type
Original Paper
Information
Psychometrika , Volume 50 , Issue 3 , September 1985, pp. 349 - 364
Copyright
Copyright © 1985 The Psychometric Society

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Footnotes

The research reported here was performed pursuant to Grant No. N0014-79-C-0039 with the Office of Naval Research.

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