Matching, missing data, a quasi-experiment, and causal inference–Oh my!

I’m finally dipping my does into causal inference for quasi-experiments, and my first use case has missing data. In this post we practice propensity score matching with multiply-imputed data sets, and how to compute the average treatment effect for the treated (ATT) with g-computation.