Apply Propensity Score Methods in Causal Inference -- Part 1: Stratification

This article introduces and implements the framework of propensity score method from Dehejia and Wahba (1999) "Causal Effects in Non-Experimental Studies: Reevaluating the Evaluation of Training Programs," Journal of the American Statistical Association, Vol. I will briefly go over the theories and then walk through how I implemented the stratification matching step by step. The full Python code is provided at the end of the article. The intuition of propensity score method is: instead of conditioning on the full vector of covariates Xᵢ, which can get difficult when there are many pre-treatment variables and when the treatment and comparison groups are very different, we try to condition on the propensity score estimated with Xᵢ. Propensity score matching works in the same way as covariate matching except that we match on the score instead of the covariates directly.