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Catching Up on Multilevel Modeling
Journal article   Open access   Peer reviewed

Catching Up on Multilevel Modeling

Lesa Hoffman and Ryan W Walters
Annual review of psychology, Vol.73(1), pp.659-689
2022
DOI: 10.1146/annurev-psych-020821-103525
PMID: 34982593
url
https://doi.org/10.1146/annurev-psych-020821-103525View
Published (Version of record) Open Access

Abstract

This review focuses on the use of multilevel models in psychology and other social sciences. We target readers who are catching up on current best practices and sources of controversy in the specification of multilevel models. We first describe common use cases for clustered, longitudinal, and cross-classified designs, as well as their combinations. Using examples from both clustered and longitudinal designs, we then address issues of centering for observed predictor variables: its use in creating interpretable fixed and random effects of predictors, its relationship to endogeneity problems (correlations between predictors and model error terms), and its translation into multivariate multilevel models (using latent-centering within multilevel structural equation models). Finally, we describe novel extensions-mixed-effects location-scale models-designed for predicting differential amounts of variability.
Humans Models, Statistical Models, Theoretical Multilevel Analysis

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