Here are some good starting points for causality theory. This is by no means intended to be an exhaustive list, and the resources are in no particular order. I imagine I will be updating it from time to time. Some good resources for getting started on causality, which use Judea Pearl's do-calculus approach to causality:
- Judea Pearl's 1999 IJCAI Award lecture on causality. On his website he has some more recent slides and tutorials too, but this is one of the two resources he recommends starting with.
- Judea Pearl's overview paper on causality. It is very well written and fun to read. This paper is like a short version of his "Causality" book (see below).
- Judea Pearl's Primer book on Causal Inference in Statistics (co-written with Madelyn Glymour and Nicholas P. Jewell). This is a very accessible introduction to causality and how to practically apply causal methods to data.
- Judea Pearl's book on Causality, which is much longer and more technical than the Primer, and very well written.
- Cosma Shalizi at Carnegie Mellon covers causality really well in his notes/book-in-progress "Advanced Data Analysis from an Elementary Point of View", chapters 20, and 24-28.
- The Morgan-Winship book "Counterfactuals and Causal Inference", the 2nd edition. Particularly: chapter 1.1, parts II (especially 2.1-2.5), III (especially 3.1)
- A brief overview of causal inference, focused on health-related applications, from the Causal Inference group at the Centre for Statistical Methodology of the London School of Hygiene and Tropical Medicine.
- Blog posts:
- Materials from University courses:
Some conferences, workshops, meetings and other academic venues on causality are listed below, from 2017-2018, again in no particular order: