Friday, November 20th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar:

Determination of cause is an important goal of biological studies, and genetic studies provide unique opportunities. In this introductory lecture we will frame causal inference as a missing data problem to clarify challenges, assumptions, and strategies necessary for assigning cause. We will survey the use of directed acyclic graphs (DAGs) to express causal information and to guide analytic strategies.

• Express causal inference as a missing data problem (counterfactual framework)
• Outline assumptions needed for causal inference
• Express causal information as (directed acyclic) graphs
• Outline how to use graphs to guide analytic strategy

Presented by:
Dr. Saunak Sen
Professor and Chief of Biostatistics
Department of Preventative Medicine
University of Tennessee Health Science Center

Link to course material