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Testing for Local Dependency in Dichotomous and Polytomous Item Response Models

Published online by Cambridge University Press:  01 January 2025

Edward Hak-sing Ip
Edward Hak-sing Ip*
Affiliation:
Marshall School of Business, University of Southern California
*
Request for reprints should be directed to the author at the Marshall School of Business, Information and Operations Management Department, University of Southern California, Los Angeles, CA 90089-1421. E-Mail: eip@bus.usc.edu
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Abstract

Researchers studying item response models are often interested in examining the effects of local dependency on the validity of the resulting conclusion from statistical inference. This paper focuses on the detection of local dependency. We provide a framework for viewing local dependency within dichotomous and polytomous items that are clustered by design, and present a testing procedure that allows researchers to specifically identify individual item pairs that exhibit local dependency, while controlling for false positive rate. Simulation results from the study indicate that the proposed method is effective. In addition, a discussion of its relation to other existing methods is provided.

Keywords

item response theoryitem clusterMantel-Haenzsel testmultiple inferenceNAEPDIMTESTYen's Q3

Information

Type
Articles
Information
Psychometrika , Volume 66 , Issue 1 , March 2001, pp. 109 - 132
Copyright
Copyright © 2001 The Psychometric Society

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Footnotes

The research was supported under the National Assessment of Educational Progress (Grant No. R902B990007) administered by the National Center of Education Statistics, U.S. Department of Education. This work was started when the author was at the Division of Statistics and Psychometrics at the Educational Testing Service. I thank Juliet Shaffer for her comments on the multiple testing procedure. I also thank three anonymous referees and the Associate Editor for suggestions that greatly improved the presentation of the manuscript.

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