title: Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation.
abstract: There have been numerous treatments in the clinical research literature about various design, analysis, and interpretation considerations when testing hypotheses about mechanisms and contingencies of effects, popularly known as mediation and moderation analysis. In this paper we address the practice of mediation and moderation analysis using linear regression in the pages of Behaviour Research and Therapy and offer some observations and recommendations, debunk some popular myths, describe some new advances, and provide an example of mediation, moderation, and their integration as conditional process analysis using the PROCESS macro for SPSS and SAS. Our goal is to nudge clinical researchers away from historically significant but increasingly old school approaches toward modifications, revisions, and extensions that characterize more modern thinking about the analysis of the mechanisms and contingencies of effects.
authors.affiliation: Department of Psychology, The Ohio State University, 1835 Neil Avenue, Columbus, OH 43210, USA. Electronic address: hayes.338@osu.edu.
authors.forename: Andrew F
authors.initials: AF
authors.lastname: Hayes
authors.affiliation: Department of Psychology, The Ohio State University, 1835 Neil Avenue, Columbus, OH 43210, USA. Electronic address: rockwood.19@osu.edu.
authors.forename: Nicholas J
authors.initials: NJ
authors.lastname: Rockwood
mesh_terms: D000068456:Clinical Studies as Topic / Q000379:methods*; D003627:Data Interpretation, Statistical; D006801:Humans; D008960:Models, Psychological; D012044:Regression Analysis
keywords: Interaction; Mechanisms; Mediation analysis; Moderation; Regression analysis