Linda Valeri (Harvard, Department of Biostatistics)

Carte non disponible

Explaining the Total Effect in the Presence of Multiple Mediators and Interactions

vendredi 24 novembre 2017, 9h30 - 10h30

Salle du conseil, espace Turing


Mediation analysis allows decomposing a total effect into a direct effect of the exposure on the outcome and an indirect effect operating through a number of possible hypothesized pathways. A recent study has provided formal definitions of direct and indirect effects when multiple mediators are of interest. Parametric and semi-parametric methods to estimate path-specific effects have also been described. Investigating direct and indirect effects with multiple mediators can be challenging in the presence of multiple exposure-mediator and mediator-mediator interactions. Our study provides three main contributions:

1) we obtain counterfactual definitions of interaction terms when more than one mediator is present;

2) we derive a decomposition of the total effect that unifies mediation and
interaction when multiple mediators are present; and

3) we illustrate the connection between our decomposition and the 4-way decomposition of the total effect introduced in the context of a single mediator. We employ the decomposition to investigate the interplay of adverse events and psychiatric symptoms in explaining the effect of antipsychotics on social functioning in schizophrenia patients.