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.
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