Introductory Overview Lecture: Causal Inference in Modern Statistics — Invited Special Presentation
JSM Partner Societies
Chair(s): Richard Levine, San Diego State University
Causal inference is a critical perspective for understanding the implications of decisions that are routinely made in science, policy and practice. This Introductory Overview Lecture reviews the role of causal inference in modern statistical applications and presents an overview of research designs and estimation strategies for estimating causal effects.