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Process / pipelineCausal inference / mediation and interaction

Four-Way Decomposition

The four-way decomposition, introduced by Tyler VanderWeele in 2014, unifies the two great themes of effect analysis — mediation and interaction — into a single, exhaustive partition of a total causal effect. Any total effect of an exposure on an outcome can be split into exactly four pieces: a controlled direct effect (neither mediation nor interaction), a reference interaction (interaction but no mediation), a mediated interaction (both mediation and interaction at once), and a pure indirect effect (mediation but no interaction). These four components are mutually exclusive and add up to the total effect, and they nest the familiar two-way and three-way decompositions as special cases. Formalized in counterfactual notation and developed at book length in VanderWeele's 2015 Explanation in Causal Inference, the method gives social epidemiologists a precise vocabulary for asking how much of an exposure's effect runs through a mediator, how much depends on the exposure and mediator acting together, and how much is direct.

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  1. VanderWeele, T. J. (2014). A unification of mediation and interaction: a four-way decomposition. Epidemiology, 25(5), 749-761. DOI: 10.1097/EDE.0000000000000121
  2. VanderWeele, T. J. (2015). Explanation in Causal Inference: Methods for Mediation and Interaction. New York: Oxford University Press. ISBN: 9780199325870

Kā citēt šo lapu

ScholarGate. (2026, June 23). Four-Way Decomposition of a Total Effect into Mediation and Interaction Components. ScholarGate. https://scholargate.app/lv/social-epidemiology/four-way-decomposition

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ScholarGateFour-Way Decomposition (Four-Way Decomposition of a Total Effect into Mediation and Interaction Components). Izgūts 2026-06-24 no https://scholargate.app/lv/social-epidemiology/four-way-decomposition · Datu kopa: https://doi.org/10.5281/zenodo.20539026