get_scores.multi_arm_causal_forest function

Compute doubly robust scores for a multi arm causal forest.

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.

## 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).

Returns

An array of scores for each contrast and outcome.