Causal Diagrams: Draw Your Assumptions Before Your Conclusions

Causal diagrams have revolutionized the way in which researchers ask: What is the causal effect of X on Y? They have become a key tool for researchers who study the effects of treatments, exposures, and policies. 

By summarizing and communicating assumptions about the causal structure of a problem, causal diagrams have helped clarify apparent paradoxes, describe common biases, and identify adjustment variables. 

The first part of this course is comprised of seven lessons that introduce causal diagrams and its applications to causal inference. 

The second part of the course presents a series of case studies that highlight the practical applications of causal diagrams to real-world questions from the health and social sciences.