3.1 Lecture
Researchers often have theories about possible causal processes linking multiple variables. Mediation is a particularly important example of such a process in which in an input variable, X, influences the outcome, Y, through an intermediary variable, M (the mediator). For instance, psychotherapy (X), may affect thoughts (M), which in turn affects mood (Y).
We can investigate mediation via a specific sequence of linear regression equations, but path modeling will make our lives much easier. We can use path models to simultaneously estimate multiple related regression equations. So, mediation analysis is an ideal application of path modeling. In this lecture, we consider both approaches and discuss their relative strengths and weaknesses.
As with mediation, researchers often posit theories involving moderation. Moderation implies that the effect of X on Y depends on another variable, Z. For instance, the effect of feedback (X) on performance (Y) may depend on age (Z). Older children might process feedback more effectively than younger children. Hence, the feedback is more effective for older children than for younger children, and the effect of feedback on performance is stronger for older children than for younger children. In such a case, we would say that age moderates the effect of feedback on performance.
3.1.1 Recordings
Note: In the following recordings, the slide numbers are a bit of a mess, because I made these videos by cutting together recordings that used different slide decks. My apologies to those who are particularly distracted by continuity errors.
3.1.2 Slides
You can download the lecture slides here