Mediating variables explain how an independent variable predicts an outcome, outlining the causal mechanism. Moderating variables change the strength or direction of a relationship between two variables.
Mediators tell us why or how something works, while moderators tell us when or for whom something works.
Consider this analogy: Imagine a light switch (IV) and a light bulb (DV).
- Mediator: the electrical wiring that connects the switch to the bulb, explaining how flipping the switch leads to the bulb illuminating.
- Moderator: a dimmer switch that affects the brightness of the bulb. The dimmer doesn’t explain how the electricity flows, but it does influence the strength of the relationship between the light switch and the bulb’s illumination.
Is a variable a mediator or moderator?
The key difference lies in their role in the causal relationship.
Mediators explain how or why a relationship exists, acting as a pathway between the independent and dependent variables.
Imagine a chain reaction: if A leads to B which then leads to C, then B is the mediator explaining how A causes C.
Consider a study investigating the relationship between exercise (IV) and improved mood (DV). A potential mediator could be endorphin release.
The theory would suggest that exercise leads to increased endorphin release, and this increase in endorphins, in turn, results in a more positive mood.
Unlike mediators, which explain the process by which an effect occurs, moderators simply tell us the conditions under which the effect is stronger or weaker, or even present or absent.
Moderators don’t fall in the causal pathway between an independent variable and an outcome variable.
Instead, they influence the strength or direction of the relationship between those variables.
Imagine a study examining the impact of social support (IV) on stress levels (DV). A potential moderator could be personality type, specifically introversion/extroversion.
The hypothesis might be that social support is more effective in reducing stress for introverts than for extroverts.
This suggests that the relationship between social support and stress levels depends on the individual’s personality type.
Theory and prior research should guide your hypotheses about whether a variable is a mediator or a moderator.
Think about the causal sequence and whether the variable fits as an intermediate step (mediator) or a factor that influences the relationship (moderator).
For example, coping style could be a mediator if it explains how a stressor leads to anxiety, or a moderator if it influences the strength of the relationship between the stressor and anxiety.
Moderated mediation
In statistics, it is possible for moderation and mediation to co-occur within the same model, giving rise to what is known as moderated mediation or a conditional indirect effect.
This signifies that the indirect effect of an independent variable on a dependent variable, mediated by a third variable, changes depending on the level of a fourth variable, the moderator.
The concept of moderated mediation essentially combines the principles of both moderation and mediation:
- Moderation: The relationship between two variables (e.g., an independent variable and a mediator) is altered by a moderator variable.
- Mediation: The effect of an independent variable on a dependent variable is explained by a mediator variable.
In a moderated mediation model, the moderator variable influences the strength or direction of the relationship between the independent variable and the mediator, thereby affecting the indirect effect of the independent variable on the outcome.
For instance, in a study examining the relationship between early childhood physical abuse (IV), deviant social information processing (M), and violent behavior (DV), a researcher might hypothesize that gender moderates the mediated relationship.
This could mean that the indirect effect of early childhood physical abuse on violent behavior, through deviant social information processing, is stronger for males than for females.
Moderated mediation analyses offer a more nuanced understanding of complex relationships by considering how mediators and moderators interact to shape the effects observed in research.
