Natural direct and indirect relative risk for mediation analysis

We consider a mediation setting involving a mediator which may channeling a part of the treatment effect along the causal pathway between the treatment and the primary outcome. Under a sequential ignorability assumption, we propose a recursive regression framework for binary outcomes so that the total causal relative risk can be decomposed into the natural direct and indirect relative risk by combining model parameters. Inference is performed by maximum likelihood methods.