Online Causal Inference Seminar

Free and open to the public

Tuesday, December 6, 2022 [Link to join] (ID: 996 2837 2037, Password: 386638)

• Speaker: Jose Zubizarreta (Harvard University)
• Title: Bridging Matching, Regression, and Weighting as Mathematical Programs for Causal Inference
• Discussant: Mike Baiocchi (Stanford University)
• Abstract: A fundamental principle in the design of observational studies is to approximate the randomized experiment that would have been conducted under controlled circumstances. Across the health and social sciences, statistical methods for covariate adjustment are used in pursuit of this principle. Basic methods are matching, regression, and weighting. In this talk, we will examine the connections between these methods through their underlying mathematical programs. We will study their strengths and weaknesses in terms of study design, computational tractability, and statistical efficiency. Overall, we will discuss the role of mathematical optimization for the design and analysis of studies of causal effects.