When: September 29th from 3:00-4:30 PM ET
This webinar will introduce respiratory health clinicians and researchers to the foundations of causal inference, including the potential outcomes framework, the four identifiability assumptions (consistency, exchangeability, positivity, and no interference), and directed acyclic graphs (DAGs) as practical tools for identifying confounding, selection bias, and guiding analytic decisions in observational respiratory health research.
Speakers
Dr. Cristina Longo
Assistant Professor at Université de Montreal
Cristina is a pediatric epidemiologist with expertise in pharmacoepidemiology, causal inference, and machine learning.
Dr. Albina Tskhay
Postdoctoral Researcher at The Digital Health and Network Multi-Omic Laboratory