Pretraining the R-learner by using the outcome model's active set to weight penalties in the CATE lasso reduces error and raises power when prognostic and predictive factors share support.
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Statistical Learning for Heterogeneous Treatment Effects: Pretraining, Prognosis, and Prediction
Pretraining the R-learner by using the outcome model's active set to weight penalties in the CATE lasso reduces error and raises power when prognostic and predictive factors share support.