Showing papers by "Andrew F. Hayes published in 2018"
TL;DR: The authors extended this approach to models with more than one mediator and showed that the indirect effect of a mediator depends on a fourth variable, i.e., a second mediator.
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.
1,186 citations