The intro sections and DAGs for the RD chapter are in. More to come.<\/p>\n
I’m looking for interesting datasets for the RD design. I have some candidates, but I’m eager to find more compelling, real data. Ideally, I’d like a business case (rather than policy), such as one on customer loyalty status. The IV chapter already uses policy data (tax on cigarette prices vs. smoking). Please comment with a link if you have ideas beyond the Kaggle datasets.<\/p>\n
As a reminder, Causal Book is an accessible, interactive resource for the data science and causal inference audience. It is not meant to substitute for the excellent texts already available, such as The Effect by Nick Huntington-Klein<\/em> and The Mixtape by Scott Cunningham<\/em>. This book aims to complement them by focusing on the idea of solution patterns, with code in R and Python, exploring different approaches (Freq. Statistics, Machine Learning, and Bayesian), and clarifying some of the counterintuitive (or seemingly surprising) challenges faced in practice.<\/p>\n