A Unification of Mediator, Confounder, and Collider Effects

David P. MacKinnon, Sophia J. Lamp

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Third-variable effects, such as mediation and confounding, are core concepts in prevention science, providing the theoretical basis for investigating how risk factors affect behavior and how interventions change behavior. Another third variable, the collider, is not commonly considered but is also important for prevention science. This paper describes the importance of the collider effect as well as the similarities and differences between these three third-variable effects. The single mediator model in which the third variable (T) is a mediator of the independent variable (X) to dependent variable (Y) effect is used to demonstrate how to estimate each third-variable effect. We provide difference in coefficients and product of coefficients estimators of the effects and demonstrate how to calculate these values with real data. Suppression effects are defined for each type of third-variable effect. Future directions and implications of these results are discussed.

Original languageEnglish (US)
Pages (from-to)1185-1193
Number of pages9
JournalPrevention Science
Issue number8
StatePublished - Nov 2021


  • Causal effects
  • Collider
  • Confounder
  • Mediator
  • Methods
  • Third-variable

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health


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