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On the Use of Empirical Bayes Estimates as Measures of Individual Traits.

Authors
  • Liu, Siwei1
  • Kuppens, Peter2
  • Bringmann, Laura3
  • 1 University of California at Davis, CA, USA.
  • 2 University of Leuven, Leuven, Belgium. , (Belgium)
  • 3 University of Groningen, Groningen, Netherlands. , (Netherlands)
Type
Published Article
Journal
Assessment
Publication Date
Apr 01, 2021
Volume
28
Issue
3
Pages
845–857
Identifiers
DOI: 10.1177/1073191119885019
PMID: 31672023
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Empirical Bayes (EB) estimates of the random effects in multilevel models represent how individuals deviate from the population averages and are often extracted to detect outliers or used as predictors in follow-up analysis. However, little research has examined whether EB estimates are indeed reliable and valid measures of individual traits. In this article, we use statistical theory and simulated data to show that EB estimates are biased toward zero, a phenomenon known as "shrinkage." The degree of shrinkage and reliability of EB estimates depend on a number of factors, including Level-1 residual variance, Level-1 predictor variance, Level-2 random effects variance, and number of within-person observations. As a result, EB estimates may not be ideal for detecting outliers, and they produce biased regression coefficients when used as predictors. We illustrate these issues using an empirical data set on emotion regulation and neuroticism.

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