Summarise policy-tree leaves with estimated action advantages and sample shares

Computes leaf-level summaries for a stored policy tree. Leaf advantages are estimated from doubly robust action scores and are action conditional: treated leaves report the estimated advantage of treatment relative to control, whereas control leaves report the estimated advantage of control relative to treatment.

Usage

margot_policy_leaf_summary(
  object,
  model_name,
  depth = 1L,
  weights = NULL,
  digits = 3L,
  label_mapping = NULL
)

Arguments

object

A margot_causal_forest()-style object containing results, covariates, and optionally weights.

model_name

Outcome/model name, with or without the model_ prefix.

depth

Integer policy-tree depth, usually 1 or 2.

weights

Optional evaluation weights. Defaults to object$weights.

digits

Integer; rounding used in formatted labels.

label_mapping

Optional named list used to label actions.

Value

A tibble with one row per leaf and columns for node id, action, unweighted count, weighted sample share, action-conditional estimated advantage, the legacy estimated_gain alias, and policy-value contributions.