Case Study: Causal inference for observational data using modelbased

Matching in R (III): Propensity Scores, Weighting (IPTW) and the Double Robust Estimator

In the last part of this series about Matching estimators in R, we'll look at Propensity Scores as a way to solve covariate imbalance while handling the curse of dimensionality, and to how implement a Propensity Score estimator using the `twang` package in R. We'll also explore the importance of common support, the inverse probability weighting estimator (IPTW) and the double robust estimator, which combines a regression specification with a matching-based model in order to obtain a good estimate even when there is something wrong with one of the two underlying models.