Partial, conditional, and moderated moderated mediation: Quantification, inference, and interpretation. Issue 1 (2nd January 2018)

• Record Type: Journal Article
• Authors: Hayes, Andrew F.
• Is Part Of: Communication monographs. Volume 85:Issue 1(2018)
• Page Start: 4
• Page End: 40
• Publication Date: 2018-01-02
• Subjects: Conditional process analysis -- moderated mediation -- regression analysis -- indirect effect -- PROCESS macro; Communication -- Periodicals; 302.2
• DOI: 10.1080/03637751.2017.1352100
• Languages: English
• ISSNs: 0363-7751

Abstract

ABSTRACT: Mediation of X 's effect on Y through a mediator M is moderated if the indirect effect of X depends on a fourth variable. Hayes [(2015). An index and test of linear moderated mediation. Multivariate Behavioral Research, 50, 1–22. doi:10.1080/00273171.2014.962683 ] introduced an approach to testing a moderated mediation hypothesis based on an index of moderated mediation . Here, I extend this approach to models with more than one moderator. I describe how to test if X 's indirect effect on Y is moderated by one variable when a second moderator is held constant (partial moderated mediation), conditioned on ( conditional moderated mediation ), or dependent on a second moderator ( moderated moderated mediation ). Examples are provided, as is a discussion of the visualization of indirect effects and an illustration of implementation in the PROCESS macro for SPSS and SAS.