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.




Love podcasts or audiobooks? Learn on the go with our new app.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store