Lrnr_cate_R Class

This class defines the R-learner of Xie and Wager (2021) for estimation of the conditional average treatment effect.

Format

An R6 class with public methods to initialize the learner, create a regression task, and access the base learner.

Details

For continuous treatment, this implementation follows the partially linear effect-model view in which the outcome regression is decomposed using an A * tau(X) term rather than a fully general treatment-response surface.

When the chosen modifier set V is a strict subset of the adjustment set W, the natural target is E[Y(1) - Y(0) | V] = E[tau(W) | V]. The current implementation does not generally target that object in the reduced-modifier setting. Instead, it learns the overlap-weighted projection f_R(V) = E[Var(A|W) tau(W) | V] / E[Var(A|W) | V], which simplifies to E[e(W)(1-e(W)) tau(W) | V] / E[e(W)(1-e(W)) | V] for binary treatment.

Super classes

sl3::Lrnr_base -> hte3::Lrnr_hte -> Lrnr_cate_R

Methods

Public methods

• Lrnr_cate_R$new()

• Lrnr_cate_R$get_pseudo_data()

• Lrnr_cate_R$clone()

Inherited methods

• sl3::Lrnr_base$assert_trained()
• sl3::Lrnr_base$base_chain()
• sl3::Lrnr_base$base_predict()
• sl3::Lrnr_base$base_train()
• sl3::Lrnr_base$chain()
• sl3::Lrnr_base$custom_chain()
• sl3::Lrnr_base$get_outcome_range()
• sl3::Lrnr_base$get_outcome_type()
• sl3::Lrnr_base$predict()
• sl3::Lrnr_base$predict_fold()
• sl3::Lrnr_base$print()
• sl3::Lrnr_base$process_formula()
• sl3::Lrnr_base$reparameterize()
• sl3::Lrnr_base$retrain()
• sl3::Lrnr_base$sample()
• sl3::Lrnr_base$set_train()
• sl3::Lrnr_base$subset_covariates()
• sl3::Lrnr_base$train()
• sl3::Lrnr_base$train_sublearners()
• hte3::Lrnr_hte$check_treatment_type()
• hte3::Lrnr_hte$get_modifiers()
• hte3::Lrnr_hte$make_metalearner_task()

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Method new()

Usage

Lrnr_cate_R$new(base_learner, ...)

Arguments

base_learner

A sl3 learner object inheriting from Lrnr_base that specifies the base supervised learning algorithm used by the meta-learner.

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Method get_pseudo_data()

Usage

Lrnr_cate_R$get_pseudo_data(hte3_task, ...)

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Method clone()

The objects of this class are cloneable with this method.

Usage

Lrnr_cate_R$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.