Statistical power problems with moderated multiple regression in management research
Generate an AI Snapshot to get a quick, structured summary of this paper.
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
Due to the increasing importance of moderating (i.e., interaction) effects, the use of moderated multiple regression (MMR) has become pervasive in numerous management specialties such as organizational behavior, human resources management, and strategy, to name a few. Despite its popularity, recent research on the MMR approach to moderator variable detection has identified several factors that reduce statistical power below acceptable levels and, consequently, lead researchers to erroneously dismiss theoretical models that include moderated relationships. The present article (1) briefly describes MMR, (2) reviews factors that affect the statistical power of hypothesis tests conducted using this technique, (3) proposes solutions to low power situations, and (4) discusses areas and problems related to MMR that are in need of further investigation. If we want to know how well we are doing in the biological, psychological, and social sciences, an index that will serve us well is how far we have advanced in our understanding of the moderator variables of our field -Hall & Rosenthal, 1991, p. 447.
