matheusfacure / python-causality-handbook

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
https://matheusfacure.github.io/python-causality-handbook/landing-page.html
MIT License
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Issue on page /23-Challenges-with-Effect-Heterogeneity-and-Nonlinearity.html #306

Closed curtis-lu closed 1 year ago

curtis-lu commented 1 year ago

There are some typos in the first paragraph:

Pretidting treatment effect at the unit level is extremely difficult due to the lack of ground truth. Since we only observe one potential outcome , we can’t directly estimate it. Rather, we have to relly on target tranformations (that can also be viwed as cleverly designed loss function) to estimate conditional treatment effects only in expecation. But that is not the only chalange.

Predicting treatment effect at the unit level is extremely difficult due to the lack of ground truth. Since we only observe one potential outcome, we can’t directly estimate it. Rather, we have to rely on target transformations (that can also be viewed as cleverly designed loss function) to estimate conditional treatment effects only in expectation. But that is not the only challenge.