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An Investigation of Hierarchical Bayes Procedures in Item Response Theory

Published online by Cambridge University Press:  01 January 2025

Seock-Ho Kim ,
Allan S. Cohen ,
Frank B. Baker ,
Michael J. Subkoviak  and
Tom Leonard
Seock-Ho Kim*
Affiliation:
University of Wisconsin—Madison
Allan S. Cohen
Affiliation:
University of Wisconsin—Madison
Frank B. Baker
Affiliation:
University of Wisconsin—Madison
Michael J. Subkoviak
Affiliation:
University of Wisconsin—Madison
Tom Leonard
Affiliation:
University of Wisconsin—Madison
*
Requests for reprints should be sent to Seock-Ho Kim, Testing and Evaluation, 1025 West Johnson Street, Madison, WI 53706.
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Abstract

Hierarchical Bayes procedures for the two-parameter logistic item response model were compared for estimating item and ability parameters. Simulated data sets were analyzed via two joint and two marginal Bayesian estimation procedures. The marginal Bayesian estimation procedures yielded consistently smaller root mean square differences than the joint Bayesian estimation procedures for item and ability estimates. As the sample size and test length increased, the four Bayes procedures yielded essentially the same result.

Keywords

Bayes estimationhierarchical prioritem response theoryjoint Bayesian estimationmarginal Bayesian estimation

Information

Type
Original Paper
Information
Psychometrika , Volume 59 , Issue 3 , September 1994 , pp. 405 - 421
Copyright
Copyright © 1994 The Psychometric Society

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Footnotes

The authors wish to thank the Editor and anonymous reviewers for their insightful comments and suggestions.

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