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

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  • Steffen Nestler

    (University of Münster)

  • Mitja D. Back

    (University of Münster)

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.

Suggested Citation

  • Steffen Nestler & Mitja D. Back, 2017. "Using Cross-Classified Structural Equation Models to Examine the Accuracy of Personality Judgments," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 475-497, June.
    • Handle: RePEc:spr:psycho:v:82:y:2017:i:2:d:10.1007_s11336-015-9485-6
    DOI: 10.1007/s11336-015-9485-6
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    References listed on IDEAS

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    2. David Rogosa & Hilary Saner, 1995. "Reply to Discussants: Longitudinal Data Analysis Examples With Random Coefficient Models," Journal of Educational and Behavioral Statistics, , vol. 20(2), pages 234-238, June.
    3. David Rogosa & Hilary Saner, 1995. "Longitudinal Data Analysis Examples With Random Coefficient Models," Journal of Educational and Behavioral Statistics, , vol. 20(2), pages 149-170, June.
    4. Roderick McDonald, 1993. "A general model for two-level data with responses missing at random," Psychometrika, Springer;The Psychometric Society, vol. 58(4), pages 575-585, December.
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