Mediation & moderation
In this 2-day course the core issues of mediation and moderation are explored and practiced.
- Target group
- PhD candidate
- Elise Dusseldorp (Associate Professor) Peter de Heus (Assistant Professor)
Enrollment deadline is 8 June 2019.
Within PhD projects, questions often arise about how an effect becomes stronger or weaker due to some 3rd variable ('moderation'), or how an effect may be explained by some intermediate third variable ('mediation').
The 1st day of the course is targeted at the 'basic concepts' of mediation and moderation (causal steps approach, estimating and testing indirect effects, effect size, generalisation to multiple mediators/moderators, post hoc probing of moderator effects). On the 2nd day combinations of moderation and mediation ('moderated mediation') will be discussed, not only as a direct extension and integration of day 1 topics, but also in the new context of 'within-subjects' designs.
During both days, lectures are intermingled with computer practical sessions using SPSS in combination with SPSS macros PROCESS and MEMORE.
After this course, you are able to:
- understand and explain the most important concepts of mediation and moderation, and
- perform mediation and moderation analyses with SPSS, PROCESS and MEMORE.
Basic knowledge about regression analysis, and to a lesser extent, ANOVA and ANCOVA, and basic skills in working with SPSS.
- Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis. A regression-based approach. New York: Guilford.
- A few journal articles (to be announced).