back to basics with mixed-effects models: nine take-away points

Multilevel mixed effects models are widely used in organizational behavior and organizational psychology to test and advance theory. at times, however, the complexity of the models leads researchers to draw erroneous inferences or otherwise use the models in less than optimal ways. we present nine take-away points intended to enhance the theoretical precision and utility of the models. we demonstrate our points using two types of simulated data: one in which group membership is irrelevant, and the other in which relationships exist only because of group membership. we then demonstrate that the effects we observe in simulated data replicate in organizational data. little that we address will be new to methodology experts; nonetheless, we draw together a variety of points that we believe will help advance both theory and analytic rigor in multilevel analyses. we make two points that run somewhat counter to conventional norms. first, we argue that mixed-effects models are appropriate even when icc(1) values associated with the outcome data are small and non-significant. second, we show that high icc(2) values are not a prerequisite for detecting emergent multilevel relationships. the article is designed to be a resource for researchers who are learning about and applying mixed-effects (i.e., multilevel) models.