A2073
Title: Where best to intervene
Authors: Caleb Miles - Columbia University (United States) [presenting]
Abstract: One common motivation for mediation analysis is to help identify promising avenues for future interventions in order to improve the efficacy of an exposure or to mitigate a harmful effect or disparity. That is, mediation analysis is thought to help address the question ``Where best to intervene?''. Mediation analysis formalizes this notion, which naturally leads to causal estimands that can inform about the effects of certain future (generally stochastic) interventions on unobserved variables along causal pathways. Some of these interventions correspond to so-called \emph{randomized interventional analogs} of natural direct and indirect effects and path-specific effects. Unlike so-called \emph{natural} mediation effects, these effects are manipulable in the sense that they comport with the target trial principle; that is, they are estimable in a hypothetical future randomized trial. Furthermore, their identification does not rely on any cross-world counterfactual independence assumptions. Lastly, these effects contain so-called \emph{separable effects} as a special case.
