A quasi-experiment is an empirical interventional study used to estimate the causal impact of an intervention on target population without random assignment. —Wikipedia

In this tutorial, we use simple datasets to illustrate two quasi-experimental methods: Propensity Score Matching (PSM) and Difference-in-differences (DID). We focus on the practical side of applying the methods and provide code in both Python and R via Kaggle (see links below).

This is joint work with my friend Dr. Gang Wang.

Read the full tutorial at https://harrywang.me/psm-did

*Originally published at **https://harrywang.me** on June 1, 2022.*