Introduces causal inference methods for measured confounding, covering IPTW, g-computation, and their practical application in R.
Continue readingAdvances in causal inference methods applied to real-world evidence (Part 2)
Advances in causal inference methods applied to real-world evidence (Part 1)
Introduces causal inference principles, identifiability assumptions, and DAGs for addressing confounding and bias in respiratory health research.
Continue readingLeveraging environmental data for respiratory health research
When: February 24th, 2026
Join Dr. Dany Doiron and Joey Syer as they introduce and discuss the use of the Canadian Urban Environmental Health Research Consortium (CANUE) for respiratory research.
Speakers
Dr. Dany Doiron
Assistant Professor in the Department of Environmental and Occupational Health at the University of Montreal and the Managing Director of CANUE
Dr. Joey Syer
CANUE Data Director and a part-time course professor at Fanshawe College