Exposure-induced mediator–outcome confounders in causal mediation: implications and visualisation

In their thoughtful review on causal mediation methods, Pearce et al 1 highlighted the challenges posed by exposure-induced mediator–outcome confounders for identifying natural direct and indirect effects.2 Here, we briefly provide a broader perspective on this issue using causal directed acyclic graphs (DAGs). We let A denote an exposure, Y an outcome, M a mediator and L an exposure-induced mediator–outcome confounder (figure 1a). In the counterfactual framework, we let ![Formula][1]</img> denote the potential outcomes of Y if, possibly contrary to fact, there had been interventions to set A to a and to set M to m . Similarly, we let ![Formula][2]</img> and ![Formula][3]</img> denote the potential outcomes of M and L , respectively, had A been set … [1]: /embed/mml-math-1.gif [2]: /embed/mml-math-2.gif [3]: /embed/mml-math-3.gif