PHS 7035 - Theory of Modern Causal Inference

This course offers students an in-depth exploration of the evolving statistical landscape of causal inference, which has undergone significant advancements in recent years, Within the course, we will delve into the statistical assumptions and techniques employed for estimating and drawing conclusions about causal relationships from data, either derived from randomized experiments or observational studies. Our primary objective is to equip students with a robust theoretical foundation for critically evaluating causal claims within empirical research. Throughout the course, students will develop the ability to differentiate between causal and pure associational relationships. We will conduct a comprehensive survey of state-of-the-art methods, encompassing propensity score techniques and machine learning approaches, allowing students to estimate various causal effects in both time-independent and time-varying settings.