Feature selection in stratification estimators of causal effects: lessons from potential outcomes, causal diagrams, and structural equations

no code implementations • 23 Sep 2022 • P. Richard Hahn, Andrew Herren

What is the ideal regression (if any) for estimating average causal effects?

feature selection regression

Statistical Aspects of SHAP: Functional ANOVA for Model Interpretation

1 code implementation • 21 Aug 2022 • Andrew Herren, P. Richard Hahn

We use this connection to show that challenges in SHAP approximations largely relate to the choice of a feature distribution and the number of $2^p$ ANOVA terms estimated.

Semi-supervised learning and the question of true versus estimated propensity scores

1 code implementation • 14 Sep 2020 • Andrew Herren, P. Richard Hahn

According to this formulation, large unlabeled data sets could be used to estimate a high dimensional propensity function and causal inference using a much smaller labeled data set could proceed via weighted estimators using the learned propensity scores.

Causal Inference