Longitudinal Cognitive Trajectory Modelling and Phenotyping with Multiple Features using Health Administrative Data
This project aims to develop and apply both model-based and algorithm-based statistical and machine learning methods to longitudinal trajectory clustering of multiple repeatedly measured features of cognitive decline.
Lead: Kuan Liu
Affiliates: Geoffrey M. Anderson
Bayesian sensitivity analyses for time-dependent unmeasured confounding
The strongly ignorable treatment assignment assumption (also known as no unmeasured confounding) is an untestable causal assumption which requires a sufficiently large set of covariates being measured to ensure that subjects are exchangeable across the observed exposure given measured covariates […]
Lead: Kuan Liu
Investigating regional trends in electronic cigarette consumption in Canada and identifying geographical characteristics associated with high consumption
This study investigates the prevalence of e-cigarette consumption and neighbourhood/community characteristics across Canada.
Lead: Kuan Liu
Affiliates: Aya Mitani
Consideration of Trade-offs Regarding COVID-19 Containment Measures in the United States: Implications for Canada
This study attempts to find if stimulus packages can be deemed cost-effective and whether shutdown measures are too restrictive resulting in massive economic shock to individuals.
Lead: Mayvis Rebeira
Affiliates: Eric Nauenberg
Paediatric Economic Database Evaluation (PEDE) Project
The PEDE Project provides tools and promotes research to advance the field of child health economic evaluation. The PEDE database contains detailed information on over 4,000 paediatric economic evaluations published over the past 40 years
Lead: Wendy J. Ungar
HAD5318H
Advanced Evidence Synthesis
HAD5319H
Biostatistics III: Advanced Biostatistical Techniques for Observational Studies
HAD6360H
Research Internship
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Communications
Marielle Boutin
Email Address: ihpme.communications@utoronto.ca