What is the Difference Between Moderation and Mediation?

Moderation and mediation are two distinct statistical techniques used in the field of causal inference, and they serve different purposes. Here are the main differences between them:

• Purpose: Mediation analysis focuses on the causal pathway between an independent variable (IV) and a dependent variable (DV), explaining how and why an effect occurs. In contrast, moderation analysis examines how a moderator variable affects the relationship between an independent and dependent variable, identifying under which conditions an effect occurs.
• Definition: A mediator is a variable that explains the process through which two variables are related, signing the causal relationship between the independent and dependent variables. A moderator, on the other hand, is a variable that influences the strength, direction, or presence of a relationship between variables, showing for whom, when, or under what circumstances a relationship will hold.
• Relationship with other variables: In a mediation relationship, an arrow is drawn from the independent variable to the dependent variable, and then from the independent variable to the mediator, which in turn affects the dependent variable. In a moderation relationship, an arrow is drawn from the moderator to the relationship between the independent and dependent variables, indicating that the moderator changes the strength of the relationship.

In summary, mediation analysis helps to understand the mechanism through which an independent variable affects a dependent variable, while moderation analysis helps to identify the conditions under which the relationship between an independent and dependent variable holds.

Comparative Table: Moderation vs Mediation

Here is a table summarizing the differences between moderation and mediation:

In summary, moderators affect the strength and direction of a relationship between variables, while mediators explain the causal process through which one variable influences another.