A presentation of a variety of causal inference methods as well as the business case scenarios for which they can be the most effective.

Propensity Score Matching

June 17, 2020

How can an analyst 'control' for a large number of confounding variables when they are analyzing causal effects in an observational setting, and have very little control over which individuals receive which treatment?

Causal Tree Learning For Heterogeneous Treatment Effect Estimation

July 27, 2020

Analysts are often interested how a particular intervention differentially affects individuals within an observed population, given high dimensional data describing each individual's characteristics. In this scenario, what state of the art machine learning technique is best suited for estimating heterogeneous treatment effects?