LEARNING OBJECTIVES
- Participants will learn about the potential outcomes framework and directed acyclic graphs (DAGs).
- Participants will understand the challenges to making causal claims using observational data.
- Trial emulation will be described as a framework for obtaining causal inference from observational studies. Participants will learn about target trial components such as trial eligibility, treatment assignment procedures, defining study follow-up, and determining outcomes. Finally, causal contrasts of interest will be described along with the need for careful analytic plans.
PRESENTER(S)
Nandita Mitra, PhD, is Professor of Biostatistics and Vice-Chair of Faculty Professional Development in the Department of Biostatistics, Epidemiology, and Informatics at the University of Pennsylvania. She is also the Chair of the Graduate Group in Epidemiology and Biostatistics and Co-Director of the Center for Causal Inference at Penn. Her primary research area is causal inference with a focus on developing propensity score, instrumental variables, and sensitivity analysis methods for observational data with applications in cancer, health policy, and health economics. Dr. Mitra is Editor-in-Chief of Observational Studies and serves on the editorial board of the International Journal of Biostatistics. She is an elected Fellow of the American Statistical Association.