R-Ladies Philly: Analyzing Experiments Using Causal Forests

This is an R-Ladies Philly event. RSVP on their meetup page to get the Zoom Link: https://www.meetup.com/rladies-philly/events/292812621/

R-Ladies Philly Event:
Please join us May 17th for a virtual workshop on 'Analyzing Experiments Using Causal Forests' with Elea McDonnell Feit, Associate Professor of Marketing at Drexel University.

Randomized experiments that compare two "treatments" are used in dozens of industries from clinical trials in medicine to A/B tests in marketing. Traditionally, statisticians have focused on the *average* effect of the treatment. However, we know that not everyone is average. Causal Forests is a powerful machine learning method used to find subgroups that have different (heterogeneous) treatment effects. For example, in a medical study patients with different health conditions may respond differently to a treatment. Causal Forests allows us to find those subgroups even when we have many different variables describing the patients and we don't know which ones are related to the treatment effect. Causal Forests can even be used to obtain a causal estimate of the treatment effect from observational (non-randomized) data. Elea will provide and overview of the algorithm and demonstrate how it can be implemented in R using the grf package. By the end of the talk, attendees will have a solid understanding of the theory and implementation of Causal Forests and be ready to apply this method to their own research.

PRIZE ANNOUNCEMENT:
RSVP and get entered into a raffle for a FREE eBook titled 'Tidy Modeling with R' By Max Kuhn, Julia Silge (2022). 3 winners will be chosen at the end of the workshop. If you already RSVP'd then you have been entered into the raffle. Must RSVP before the event begins to be entered in the drawing and must be present to receive the prize!