How far can exchangeability get us toward agreeing on individual probability?

Statistical Modeling, Causal Inference, and Social Science 2025-01-17

Summary:

This is Jessica. What’s the common assumption behind the following?  Partial pooling of information over groups in hierarchical Bayesian models  In causal inference of treatment effects, saying that the outcome you would get if you were treated (Y^a) shouldn’t change … Continue reading

Link:

https://statmodeling.stat.columbia.edu/2025/01/17/how-far-can-exchangeability-get-us-toward-agreeing-on-individual-probability/

From feeds:

Statistics and Visualization » Statistical Modeling, Causal Inference, and Social Science

Tags:

analysis

Authors:

Jessica Hullman

Date tagged:

01/17/2025, 15:43

Date published:

01/17/2025, 12:39