Online Causal Inference Seminar

Free and open to the public

Tuesday, June 21, 2022 [Link to join] (ID: 996 2837 2037, Password: 386638)

• Speaker: Geneviève Lefebvre (Université du Québec à Montréal)
• Title: Bayesian joint modeling for causal mediation analysis with a binary outcome and a binary mediator
• Discussant: Olli Saarela (University of Toronto)

• Abstract: Mediation analysis with a binary outcome is notoriously more challenging than with a continuous outcome. In this talk, I will present a new approach, named t-link, to perform causal mediation with a binary outcome and a binary mediator. This approach relies on the Bayesian multivariate logistic regression model introduced by O'Brien and Dunson (Biometrics, 2004, 739-746, 60(3)) and its Student-t approximation. By re-expressing the mediation formula, I show how to use this multivariate latent model for estimating the natural direct and indirect effects of an exposure on an outcome in any measure scale of interest (e.g., odds or risk ratio, risk difference). The t-link mediation approach has several valuable features which, to the best of knowledge, are not found together in existing binary-binary mediation analysis approaches. In particular, it allows for sensitivity analyses regarding the impact of unmeasured mediator-outcome confounders on the natural effects estimates. The proposed mediation approach is evaluated and compared with two other benchmark approaches using simulated data, and is illustrated using pediatric cancer data.