Decomposition of the Total Effect for Two Mediators: A Natural Counterfactual Interaction Effect Framework

TL;DR

This paper introduces a new framework for decomposing the total causal effect in mediation analysis involving two mediators, accounting for sequential and non-sequential causal relationships and interactions.

Contribution

It develops a unified approach for decomposing effects into mediation, interaction, both, or neither, including a novel natural counterfactual interaction effect concept.

Findings

New decomposition method for two mediators with causal order

Extension of interaction effects to sequential mediators

Application to real data demonstrating the method

Abstract

Mediation analysis has been used in many disciplines to explain the mechanism or process that underlies an observed relationship between an exposure variable and an outcome variable via the inclusion of mediators. Decompositions of the total causal effect of an exposure variable into effects characterizing mediation pathways and interactions have gained an increasing amount of interest in the last decade. In this work, we develop decompositions for scenarios where the two mediators are causally sequential or non-sequential. Current developments in this area have primarily focused on either decompositions without interaction components or with interactions but assuming no causally sequential order between the mediators. We propose a new concept called natural counterfactual interaction effect that captures the two-way and three-way interactions for both scenarios that extend the two-way mediated interactions in literature. We develop a unified approach for decomposing the total effect into the effects that are due to mediation only, interaction only, both mediation and interaction, neither mediation nor interaction within the counterfactual framework. Finally, we illustrate the proposed decomposition method using a real data analysis where the two mediators are causally sequential.