On Partial Versus Full Mediation and the Importance of Effect Sizes

Abstract

Theoretical models involving one or multiple intervening variables often posit whether a cause influences an outcome both directly and indirectly or only indirectly. In testing mediation, this distinction of partial and full mediation has become a subject of debate because of statistical issues. We extend the critique on this notion and provide insights into what a statistically significant direct effect between a cause and an outcome in a mediation model can mean. We also evaluate different effect size measures for direct and indirect effects and offer practical recommendations for assessing mediation mechanisms, which we illustrate using different examples. The broader relevance of these recommendations beyond mediation analysis is discussed.