Clarifying causal mediation analysis for the applied researcher: Defining effects based on what we want to learn.

Psychological Methods
Trang Quynh NguyenElizabeth A Stuart

Abstract

The incorporation of causal inference in mediation analysis has led to theoretical and methodological advancements-effect definitions with causal interpretation, clarification of assumptions required for effect identification, and an expanding array of options for effect estimation. However, the literature on these results is fast-growing and complex, which may be confusing to researchers unfamiliar with causal inference or unfamiliar with mediation. The goal of this article is to help ease the understanding and adoption of causal mediation analysis. It starts by highlighting a key difference between the causal inference and traditional approaches to mediation analysis and making a case for the need for explicit causal thinking and the causal inference approach in mediation analysis. It then explains in as-plain-as-possible language existing effect types, paying special attention to motivating these effects with different types of research questions, and using concrete examples for illustration. This presentation differentiates 2 perspectives (or purposes of analysis): the explanatory perspective (aiming to explain the total effect) and the interventional perspective (asking questions about hypothetical interventions on the exp...Continue Reading

Citations

Aug 28, 2020·BMJ Evidence-based Medicine·Aidan G CashinHopin Lee
Feb 20, 2021·Journal of Clinical Epidemiology·Aidan G Cashin, Hopin Lee
Aug 13, 2021·Epigenetics : Official Journal of the DNA Methylation Society·Ryosuke FujiiKoji Suzuki
Aug 20, 2021·The Journal of Pain : Official Journal of the American Pain Society·Aidan G CashinJames H McAuley
Sep 22, 2021·JAMA : the Journal of the American Medical Association·Hopin LeeNicholas Henschke

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