Back to the program

Invited Paper Session

Modern Innovations in Longitudinal Causal Inference for Health Applications

Mon, Aug 4, 8:30 AM - 10:20 AM Room CC-106B Music City Center

Mohammad Ehsanul KarimOrganizerXizhen CaiChair

SSC (Statistical Society of Canada) co: Section on Statistics in Epidemiologyco: Biometrics Section Applied

5 Presentations

A Bayesian model averaging approach for estimating the parameters of longitudinal marginal structural models

8:30 AM - 8:55 AM

Denis Talbot (Universite Laval)

Co-authors: David Adenyo (Université Laval)

Causal inference Bayesian model averaging Longitudinal data Variable selection Model selection

Functional Causal Mediation Analysis with Zero-inflated Count Data

8:55 AM - 9:15 AM

Yeying Zhu (University of Waterloo)

Co-authors: Henan Xu (University of Waterloo), Donna Coffman (University of South Carolina)

Causal inference Count data Functional data analysis Mediation analysis Zero-inflation

Penalized G-estimation for effect modifier selection in a structural nested mean model for repeated outcomes

9:15 AM - 9:35 AM

Ajmery Jaman (McGill University)

Co-authors: Guanbo Wang (Harvard University), Ashkan Ertefaie (University of Pennsylvania), Michèle Bally (Centre Hospital of University of Montreal), Renée Lévesque (University of Montreal), Robert W. Platt (McGill University), Mireille Schnitzer (Université de Montréal)

double robustness effect modifier selection G-estimation hemodiafiltration longitudinal observational data penalization

Finite sample and asymptotic behaviour of the longitudinal outcome-highly-adaptive LASSO

9:35 AM - 9:55 AM

Mireille Schnitzer (Université de Montréal)

causal inference longitudinal time-dependent nonparametric machine-learning

Optimizing visit times to improve hypertension management, an application to the SPRINT trial

9:55 AM - 10:15 AM

Janie Coulombe (Université de Montréal)

Dynamic treatment regimes Optimal monitoring times Causal inference Longitudinal data Missing data Hypertension care

↑