Parametric and semiparametric estimation methods are available for the case of multiple mediators in causal mediation analysis. However, in the presence of multiple exposure-mediators and mediator-mediator interactions, it is challenging to study the direct and indirect effects of multiple mediators. In this paper, we use G-computation to derive a decomposition of the overall effect that unifies the mediating and interacting effects when multiple mediators are present, including natural direct and indirect effects, direct effects of standard and random controls, and reference and mediating int...
