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On the Use of Heterogeneous Thresholds Ordinal Regression Models to Account for Individual Differences in Response Style

Published online by Cambridge University Press:  01 January 2025

Timothy R. Johnson
Timothy R. Johnson*
Affiliation:
Department of Statistics, University of Idaho
*
Requests for reprints should be sent to Timothy R. Johnson, Department of Statistics, University of Idaho, Moscow, ID 83844-1104, USA. Email: trjohns@uidaho.edu
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Abstract

This paper proposes a general approach to accounting for individual differences in the extreme response style in statistical models for ordered response categories. This approach uses a hierarchical ordinal regression modeling framework with heterogeneous thresholds structures to account for individual differences in the response style. Markov chain Monte Carlo algorithms for Bayesian inference for models with heterogeneous thresholds structures are discussed in detail. A simulation and two examples based on ordinal probit models are given to illustrate the proposed methodology. The simulation and examples also demonstrate that failing to account for individual differences in the extreme response style can have adverse consequences for statistical inferences.

Keywords

response styleordinal regressionhierarchical regression modelsprobit modelsBayesian statistics

Information

Type
Theory And Methods
Information
Psychometrika , Volume 68 , Issue 4 , December 2003 , pp. 563 - 583
Copyright
Copyright © 2003 The Psychometric Society

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Footnotes

The author is grateful to Ulf Böckenholt, an associate editor, and three anonymous reviewers for helpful comments, and Kristine Kuhn and Kshiti Joshi for providing the data.

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