Communication Monographs· 2017Q1
Partial, conditional, and moderated moderated mediation: Quantification, inference, and interpretation
- 3,266citations
- Q1SCImago
- 2017year
Short summary
This paper extends existing methods to test complex mediation models where the indirect effect of a variable X on Y is influenced by multiple moderators.
AI-generated from the title and abstract; the full text is not read.
Key points
- Extends moderated mediation analysis to models with multiple moderators.
- Introduces methods for partial, conditional, and moderated moderated mediation.
- Provides quantification, inference, and interpretation strategies for these complex models.
- Includes examples and implementation details for SPSS and SAS.
AI-generated from the title and abstract; the full text is not read.
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.
The authors' abstract, as published at the source. Communication Monographs, 2017 · DOI ↗
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Field: Applied Psychology
Applied PsychologyPsychology