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On the Need for Negative Local Item Dependence

Published online by Cambridge University Press:  01 January 2025

Brian Habing and
Louis A. Roussos
Brian Habing*
Affiliation:
Department of Statistics, University of South Carolina
Louis A. Roussos
Affiliation:
Department of Educational Psychology, University of Illinois at Urbana-Champaign
*
Requests for reprints should be sent to Brian Habing, Department of Statistics, University of South Carolina, Columbia SC 29208. E-Mail: habing@stat.sc.edu
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Abstract

While negative local item dependence (LID) has been discussed in numerous articles, its occurrence and effects often go unrecognized. This is due in part to confusion over what unidimensional latent trait is being utilized in evaluating the LID of multidimensional testing data. This article addresses this confusion by using an appropriately chosen latent variable to condition on. It then provides a proof that negative LID must occur when unidimensional ability estimates (such as number right score) are obtained from data which follow a very general class of multidimensional item response theory models. The importance of specifying what unidimensional latent trait is used, and its effect on the sign of the LIDs are shown to have implications in regard to a variety of foundational theoretical arguments, to the simulation of LID data sets, and to the use of testlet scoring for removing LID.

Keywords

item response theoryconditional covariancedimensionalitygeneralized compensatory modellatent traitlocal independencelocal item dependenceMantel-HaenszelmultidimensionalityQ3testlet

Information

Type
Article
Information
Psychometrika , Volume 68 , Issue 3 , September 2003, pp. 435 - 451
Copyright
Copyright © 2003 The Psychometric Society

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Footnotes

This paper is based in part on a chapter in the first author's doctoral dissertation, written at the University of Illinois at Urbana-Champaign under the supervision of William Stout. Part of this research has been presented at the annual meeting of the National Council on Measurement in Education, San Diego, California, April 14–16, 1998.

The research of the first author was partially supported by a Harold Gulliksen Psychometric fellowship through Educational Testing Service and by a Research and Productive Scholarship award from the University of South Carolina.

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