estimate causal Tree
estimate.causalTree(
object,
data,
weights,
treatment,
na.action = na.causalTree
)Intermediate estimation results for an causalTree object
A tree-structured fit rpart object, such as one
generated as a causalTree fit.
New data frame to be used for estimating effects within leaves.
optional case weights.
The treatment status of observations in the new dataframe, where 1 represents treated and 0 represents control.
the default action deletes all observations for which
y is missing, but keeps those in which one or more predictors
are missing.
When the leaf contains only treated or control cases, the function will trace back to the leaf's parent node recursively until the parent can be used to compute causal effect. Please see Athey and Imbens Machine Learning Methods for Estimating Heterogeneous Causal Effects (2015) for details.