Dealing with Time-Varying Confounding in Mediation Analysis

• Activity Number: 484
• Type: Invited
• Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Stijn Vansteelandt*+
• Companies: Ghent University
• Keywords: mediation ; causal inference ; double robustness ; time-varying confounding

Abstract

Mediation analysis is frequently utilized in diverse scientific fields to develop insight into the causal mechanism whereby an exposure affects an outcome. Despite its popularity, the traditional approach to mediation analysis proceeds in a predominantly heuristic fashion, which can largely be ascribed to the lack of precise definitions of direct and indirect effect in the traditional mediation analysis literatures. Moreover, problems of confounding bias have been largely ignored.

Robins, Greenland and Pearl laid the foundations for a rigorous approach towards mediation analysis, which is based on counterfactuals. They gave precise definitions of direct and indirect effect and elucidated the kind of data that must be collected in order to control for confounding bias. In this presentation, I will concentrate on the - partly unsolved - methodological challenges that arise when confounders of the mediator-outcome association are affected by the exposure. In particular, I will present results on the the the identification of (natural) direct and indirect effects in such settings, and on the estimation of (controlled) direct effects, thereby focussing on matched case-control studies.