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Assessing Statistical Accuracy in Ability Estimation: A Bootstrap Approach

Published online by Cambridge University Press:  01 January 2025

Michelle Liou  and
Lien-Chi Yu
Michelle Liou*
Affiliation:
Academia Sinica, University of California, Berkeley
Lien-Chi Yu
Affiliation:
North Carolina State University, Raleigh
*
Requests for reprints should be sent to Michelle Liou, Institute of Statistical Science, Academia Sinica, Taipei 11529, Taiwan, R.O.C.
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Abstract

Given known item parameters, the bootstrap method can be used to determine the statistical accuracy of ability estimates in item response theory. Through a Monte Carlo study, the method is evaluated as a way of approximating the standard error and confidence limits for the maximum likelihood estimate of the ability parameter, and compared to the use of the theoretical standard error and confidence limits developed by Lord. At least for short tests, the bootstrap method yielded better estimates than the corresponding theoretical values.

Keywords

ability estimatesitem response theorymaximum likelihoodstatistical accuracythe bootstrap method

Information

Type
Original Paper
Information
Psychometrika , Volume 56 , Issue 1 , March 1991 , pp. 55 - 67
Copyright
Copyright © 1991 The Psychometric Society

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Footnotes

This paper was originally presented at the Annual Meeting of American Educational Research Association, Washington, D.C., April 1987. The authors are indebted to Patricia Busk, the editor, and two anonymous referees for helpful comments on the earlier drafts of the manuscript.

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