Sample Size Requirements for the Three-Level Multivariate Multilevel Model

• In Event: 33.058 - Effect Sizes, Sample Sizes, and Power

Abstract

The multivariate multilevel model (MVMM) is a multilevel regression approach to estimating and testing the effects of explanatory variables on a set of correlated continuous outcomes. The purpose of this study was to extend previous research on sample size requirements for maximum likelihood (ML) estimation of three-level MVMMs by including random slopes and cross-level interactions in the models. The study also compared the MVMM results to those obtained from corresponding univariate two-level hierarchical linear models (HLMs). Results indicate that sample size requirements for random-coefficients MVMMs were similar to those for HLMs across the conditions investigated in this study.

Authors

• Wanchen Chang, Boise State University

• Susan Natasha Beretvas, The University of Texas - Austin

• Keenan A. Pituch, The University of Texas - Austin