In this blog post, I describe the introductory course on Causal Inference I pieced together using various materials available online. It combines Pearl's Causal Graph approach with statistics Gelman/mcElreath style.
In this post, we test both `Bayesian Additive Regression Trees (BART)` and `Causal forests (grf)` on four simulated datasets of increasing complexity. May the best method win!