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Response Mixture Modeling: Accounting for Heterogeneity in Item Characteristics across Response Times

Published online by Cambridge University Press:  01 January 2025

Dylan Molenaar  and
Paul de Boeck
Dylan Molenaar*
Affiliation:
Psychological Methods, Department of Psychology, University of Amsterdam
Paul de Boeck
Affiliation:
Ohio State University
*
Correspondence should be made to Dylan Molenaar, Psychological Methods, Department of Psychology, University of Amsterdam, PO box 15906, 1001 NK Amsterdam, The Netherlands. Email: D.Molenaar@uva.nl
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Abstract

In item response theory modeling of responses and response times, it is commonly assumed that the item responses have the same characteristics across the response times. However, heterogeneity might arise in the data if subjects resort to different response processes when solving the test items. These differences may be within-subject effects, that is, a subject might use a certain process on some of the items and a different process with different item characteristics on the other items. If the probability of using one process over the other process depends on the subject’s response time, within-subject heterogeneity of the item characteristics across the response times arises. In this paper, the method of response mixture modeling is presented to account for such heterogeneity. Contrary to traditional mixture modeling where the full response vectors are classified, response mixture modeling involves classification of the individual elements in the response vector. In a simulation study, the response mixture model is shown to be viable in terms of parameter recovery. In addition, the response mixture model is applied to a real dataset to illustrate its use in investigating within-subject heterogeneity in the item characteristics across response times.

Keywords

item response theoryresponse time modelingmixture modeling

Information

Type
Original Paper
Information
Psychometrika , Volume 83 , Issue 2 , June 2018 , pp. 279 - 297
Copyright
Copyright © 2018 The Psychometric Society

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Footnotes

Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11336-017-9602-9) contains supplementary material, which is available to authorized users.

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