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Using Cross-Classified Structural Equation Models to Examine the Accuracy of Personality Judgments

Published online by Cambridge University Press:  01 January 2025

Steffen Nestler  and
Mitja D. Back
Steffen Nestler*
Affiliation:
University of Münster
Mitja D. Back
Affiliation:
University of Münster
*
Correspondence should be made to Steffen Nestler, University of Münster, Fliednerstr. 21, 48149 Münster, Germany. Email: steffen.nestler@wwu.de; steffen.nestler@uni-muenster.de
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Abstract

Whether, when, and why perceivers are able to accurately infer the personality traits of other individuals is a key topic in psychological science. Studies examining this question typically ask a number of perceivers to judge a number of targets with regard to a specific trait. The resulting data are then analyzed by averaging the judgments across perceivers or by computing the respective statistic for each single perceiver. Here, we discuss the limitations of the average-perceiver and single-perceiver approaches. Furthermore, we argue that and illustrate how cross-classified structural equation models can be used for the flexible analysis of accuracy data.

Keywords

personality judgmentsaccuracylens modelmixed modelscross-classified structural equation models
Type
Original Paper
Information
Psychometrika , Volume 82 , Issue 2 , June 2017 , pp. 475 - 497
Copyright
Copyright © 2015 The Psychometric Society

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Footnotes

We are grateful to Sarah Humberg for very helpful comments on an earlier version of the manuscript. This article is dedicated to Irmgard Laufer.

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