A Practical Guide to Quasi-Experimental Methods (PSM and DID)
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.