Mediation (statistics)

Simple mediation model. The independent variable causes the mediator variable; the mediator variable causes the dependent variable.

In statistics, a mediation model seeks to identify and explain the mechanism or process that underlies an observed relationship between an independent variable and a dependent variable via the inclusion of a third hypothetical variable, known as a mediator variable (also a mediating variable, intermediary variable, or intervening variable).[1] Rather than a direct causal relationship between the independent variable and the dependent variable, a mediation model proposes that the independent variable influences the mediator variable, which in turn influences the dependent variable. Thus, the mediator variable serves to clarify the nature of the causal relationship between the independent and dependent variables.[2][3]

Mediation analyses are employed to understand a known relationship by exploring the underlying mechanism or process by which one variable influences another variable through a mediator variable.[4] In particular, mediation analysis can contribute to better understanding the relationship between an independent variable and a dependent variable when these variables do not have an obvious direct connection.

  1. ^ "Types of Variables" (PDF). University of Indiana. Archived from the original (PDF) on 2020-03-31. Retrieved 2016-01-25.
  2. ^ MacKinnon, D. P. (2008). Introduction to Statistical Mediation Analysis. New York: Erlbaum.
  3. ^ VanderWeele, T.J. (2016). "Mediation analysis: a practitioner's guide". Annual Review of Public Health. 37: 17–32. doi:10.1146/annurev-publhealth-032315-021402. PMID 26653405.
  4. ^ Cohen, J.; Cohen, P.; West, S. G.; Aiken, L. S. (2003) Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (3rd ed.). Mahwah, NJ: Erlbaum.