Catching Up on Multilevel Modeling (in press, Annual Review of Psychology)

The present review focuses on the use of multilevel models in psychology and other social sciences. We target readers aiming to get up to speed 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, 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. An online supplement provides suggested introductory textbooks for getting started with multilevel modeling.