Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction

Category: Mathematics
Author: Guido W. Imbens, Donald B. Rubin
This Month Hacker News 1


by mlthoughts2018   2018-09-19
A good starting point is chapters 9 & 10 from [0]. Then many of the same topics are re-discussed in the second half of the book through the lens of Bayesian hierarchical models.

Another good reference is [1]. Rubin invented a lot of observational data methods for correcting to measure causal effect. Imbens is also a prolific author in this area, and even just googling for propensity model papers from Imbens will leads to many methods and many other papers.

[0]: < >