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Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research

Published online by Cambridge University Press:  01 January 2025

Martijn G. de Jong  and
Jan-Benedict E. M. Steenkamp
Martijn G. de Jong*
Affiliation:
RSM Erasmus University
Jan-Benedict E. M. Steenkamp
Affiliation:
University of North-Carolina at Chapel Hill
*
Requests for reprints should be sent to Martijn G. de Jong, Department of Marketing Management, RSM Erasmus University, Room T10-17, Burgemeester Oudlaan 50, Rotterdam 3062 PA, The Netherlands. E-mail: MJong@rsm.nl
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Abstract

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We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while countries within these groups are still allowed to be heterogeneous. A simulation study is conducted that shows that all parameters can be recovered. We also apply the model to real data on the two components of affective subjective well-being: positive affect and negative affect. The psychometric behavior of these two scales is studied in 28 countries across four continents.

Keywords

measurement equivalencemeasurement invariancemixture modelinglatent classesdifferential item functioningitem response theoryhierarchical item response theorymultidimensional IRTgraded response modelcross-cultural research

Information

Type
Theory and Methods
Information
Psychometrika , Volume 75 , Issue 1 , March 2010 , pp. 3 - 32
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NC
This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
Copyright
Copyright © 2009 The Psychometric Society

Footnotes

We thank AiMark for providing the data, and Roger Millsap, Bengt Muthén, and the anonymous reviewers for extremely valuable comments.

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