On this page, I share some resources I find interesting. With causality very much on my mind these days, the first entry is for my recommendations on this topic.
Causality Recommendations
For those who are interested in causal inference, here are a couple of resources three of which are free*:
Judea Pearl has three books on causality. The Book of Why is aimed at a general audience and is a great starting point. To go deeper, one can read the other two books by Pearl:
- Pearl, Judea, and Dana Mackenzie. The Book of Why: The New Science of Cause and Effect. 1st edition. Basic Books, 2018.
For a short and sweet programming article:
- *Molak, Aleksander. “Causal Python: 3 Simple Techniques to Jump-Start Your Causal Inference Journey Today.” Medium, October 28, 2022.
Here are a few free resources:
- *Huntington-Klein, Nick. The Effect: An Introduction to Research Design and Causality which has an accompanying video series.
Hernán and Robins’s book includes longitudinal data analysis:
- *Hernán, Miguel A., and James M. Robins. Causal Inference: What If. Boca Raton: Chapman & Hall/CRC., 2020.