Design and Analysis: Paradox of Bayesian Propensity Scores
regression
propensity scores
causal inference
Abstract
Paradox of Bayesian Propensity Estimation
The Paradox of Bayesian Propensity
In this project I sought to outline the process of justifying the use of propensity scores in bayesian outcome regressions in CausalPy. We emphasised the role of propensity scores in Bayesian inference. The focus was on the manner in which the estimation of a causal treatment effects using propensity scores require a two-stage strategy to avoid biasing the propensity score distribution. The demonstration can be seen here.
