Mediation Analysis Explained: How Indirect Effects Reveal Research Mechanisms

Researchers often want to know not just whether two variables are related, but how one influences the other. Mediation analysis tests whether an intermediate variable, or mediator, helps explain that link, using an example in which social media marketing may affect purchase intention through brand awareness. The approach relies on two paths: the effect of the independent variable on the mediator, and the effect of the mediator on the outcome, whose product gives the indirect effect. Because the indirect effect's sampling distribution is often non-normal, researchers typically use bootstrap confidence intervals to assess its uncertainty. The guide also cautions that finding an indirect effect does not by itself establish causation, which depends on research design and assumptions.