Understanding Mediation Testing and Indirect Effects

Mediation testing is a statistical method used to understand the mechanism through which an independent variable affects a dependent variable via a third variable, known as the mediator. This process helps in revealing how and why certain effects occur, providing deeper insights into causal relationships.
What is Mediation?
Mediation occurs when the relationship between an independent variable (IV) and a dependent variable (DV) is explained by a third variable (mediator, M). The mediator serves as an intermediary process through which the IV influences the DV.
Components of Mediation
1. Independent Variable (IV): The variable that is manipulated or considered the cause.
2. Mediator (M): The variable that transmits the effect of the IV on the DV.
3. Dependent Variable (DV): The outcome or the effect that is being measured.
Mediation testing and indirect effects provide a nuanced understanding of the relationships between variables, helping researchers uncover underlying mechanisms in causal pathways. By identifying mediators, we can better comprehend how and why certain effects occur, leading to more effective interventions and policies.