Catching Up on Multilevel Modeling

Lesa Hoffman, Ryan W. Walters

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

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 mdash mixed-effects location-scale models mdash designed for predicting differential amounts of variability.

Original languageEnglish (US)
Pages (from-to)659-689
Number of pages31
JournalAnnual Review of Psychology
Volume73
DOIs
StatePublished - 2022

All Science Journal Classification (ASJC) codes

  • Psychology(all)

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