Estimating Statistical Power and Required Sample Sizes for Organizational Research Using Multilevel Modeling

Abstract

The use of multilevel modeling to investigate organizational phenomena is rapidly increasing. Unfortunately, little advice is readily available for organizational researchers attempting to determine statistical power when using multilevel models or when determining sample sizes for each level that will maximize statistical power. This article presents an introduction to statistical power in multilevel models. The unique factors influencing power in multilevel models and calculations for estimating power for simple fixed effects, variance components, and cross-level interactions are presented. The results of simulation studies and the existing general rules of thumb are discussed, and the available power analysis software is reviewed.