compute_meta_marg_results: Compute v-fold specific estimates and do a meta-analysis type...

In blind-contours/CVtreeMLE: Cross Validated Decision Trees with Targeted Maximum Likelihood Estimation

Compute v-fold specific estimates and do a meta-analysis type pooled average ATE for each individual marginal rule.

Description

For each fold, estimates the ATE for a fold specific mixture rule. Also estimates a meta-analysis type average ATE and pooled variance. Creates a union rule that covers all the folds in the rules.

Usage

compute_meta_marg_results(v_fold_marginal_results, data, mix_comps, n_folds)

Arguments

v_fold_marginal_results	List of dataframes for v-fold specific estimates of the fold-specific rule results for marginals
data	Input dataframe on which to evaluate the rules
mix_comps	Vector of characters indicating the mixture components
n_folds	Number of folds used in cross-validation

Value

Rules object. TODO: add more detail here.

blind-contours/CVtreeMLE documentation built on June 22, 2024, 8:53 p.m.