JSM2024
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Topic-Contributed Paper Session

Innovations in Causal Inference: Integrating Machine Learning in Health Research

Sun, Aug 4, 2:00 PM - 3:50 PM
Mohammad Ehsanul KarimChair
SSC (Statistical Society of Canada)

5 Presentations

Machine Learning to Control Confounding When Estimating an Optimal Adaptive Treatment Strategy
2:05 PM - 2:25 PM
Denis Talbot (Universite Laval)
Co-authors: Kossi Clement Trenou (Universite Laval), Miceline Mesidor (Institut national de la recherche scientifique), Aida Eslami
Causal Inference with Incomplete Exposure and Confounders
2:25 PM - 2:45 PM
Lan Wen
A Bayesian Joint Model for Mediation Analysis with Matrix-Valued Mediators
2:45 PM - 3:05 PM
Olli Saarela (University of Toronto)
Co-authors: Zijin Liu (University of Toronto), Zhihui Liu (University Health Network)
Selection of Mediators and Dependence Structure for High-dimensional Causal Mediation Analysis
3:05 PM - 3:25 PM
Yeying Zhu (University of Waterloo)
Co-authors: Lijia Wang (University of Waterloo), Richard Cook (University of Waterloo)
Bayesian Approaches to Causal Inference: The Present Position and the Path Ahead
3:25 PM - 3:45 PM
Paul Gustafson (University of British Columbia)
Co-authors: Conor Morrison (University of British Columbia), Daniel Daly-Grafstein (University of British Columbia)
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