Model Perspective
Sep 13, 2022 · Fundamentals
Why Linear Regression Is Surprisingly Powerful for Causal Inference
This article explains how linear regression can be used to estimate average causal effects, handle bias, and draw valid conclusions from both randomized experiments and observational data, while illustrating the theory with concrete examples and visualizations.
average treatment effectcausal inferencelinear regression
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