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Asymmetric Item Characteristic Curves and Item Complexity: Insights from Simulation and Real Data Analyses

Published online by Cambridge University Press:  01 January 2025

Sora Lee Open the ORCID record for Sora Lee [Opens in a new window]  and
Daniel M. Bolt
Sora Lee*
Affiliation:
University of Wisconsin
Daniel M. Bolt
Affiliation:
University of Wisconsin
*
Correspondence should be made to Sora Lee, University of Wisconsin, Madison, WI, USA. Email: slee486uw@gmail.com
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Abstract

While item complexity is often considered as an item feature in test development, it is much less frequently attended to in the psychometric modeling of test items. Prior work suggests that item complexity may manifest through asymmetry in item characteristics curves (ICCs; Samejima in Psychometrika 65:319–335, 2000). In the current paper, we study the potential for asymmetric IRT models to inform empirically about underlying item complexity, and thus the potential value of asymmetric models as tools for item validation. Both simulation and real data studies are presented. Some psychometric consequences of ignoring asymmetry, as well as potential strategies for more effective estimation of asymmetry, are considered in discussion.

Keywords

item response theoryasymmetric item characteristic curvesitem complexityitem validation
Type
Original Paper
Information
Psychometrika , Volume 83 , Issue 2 , June 2018 , pp. 453 - 475
Copyright
Copyright © 2017 The Psychometric Society

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Footnotes

Electronic supplementary material The online version of this article (doi:10.1007/s11336-017-9586-5) contains supplementary material, which is available to authorized users.

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