get_scores.multi_arm_causal_forest {grf} | R Documentation |
Compute doubly robust scores for a multi arm causal forest.
Description
Compute doubly robust (AIPW) scores for average treatment effect estimation using a multi arm causal forest. Under regularity conditions, the average of the DR.scores is an efficient estimate of the average treatment effect.
Usage
## S3 method for class 'multi_arm_causal_forest'
get_scores(forest, subset = NULL, drop = FALSE, ...)
Arguments
forest |
A trained multi arm causal forest. |
subset |
Specifies subset of the training examples over which we estimate the ATE. WARNING: For valid statistical performance, the subset should be defined only using features Xi, not using the treatment Wi or the outcome Yi. |
drop |
If TRUE, coerce the result to the lowest possible dimension. Default is FALSE. |
... |
Additional arguments (currently ignored). |
Value
An array of scores for each contrast and outcome.
[Package grf version 2.3.2 Index]