A moderator is a qualitative or quantitative variable that affects the direction and/or strength of the relation between an IV (or predictor) and a dependent or criterion variable.
Within a correlational analysis framework, a moderator is a third variable that affects the zero-order correlation between two other variable. In the more familiar ANOVA terms, a basic moderator effect can be represented as an interaction between a focal IV and a factor that specifies the appropriate conditions for its operation. In other words, an observed relationship may be different at different levels of a third variable. Moderation refers to the situation where the direction and intensity of an effect of a predictor on a criterion depends on the levels or settings of a third variable. In essence, moderators attenuate or exacerbate the effect.
- Variables entered into the regression equation in a stepwise and hierarchical fashion.
- Control variables (if any were collected) are entered first into the equation.
- In order to derive main effects of X on Y, regress X onto Y for this step
- Add the interaction terms (X x M) to the analysis. If there is a change in total variance explained from step 3 to step 4 this suggests total moderational impact, and r2 values for each interaction term shows the impact of the moderator for each relationship.
- X correlates with Y
- X correlates with M
- M significant impact on Y when X controlled for
- Effect of X on Y when M controlled for is 0 for full mediation