Average treatment effect of a fitted CATE model

Averages the CATE predictions of a fitted meta-learner over the rows of newdata: $$\widehat{ATE} = \frac{1}{n} \sum_i \hat\tau(x^{(i)})$$

ate(object, ...)

# S3 method for class 'cate_learner'
ate(object, newdata, ...)

Arguments

object

A fitted CATE model, e.g. from s_learner().

...

Passed on to methods.

newdata

A data.frame containing at least the covariate columns.

Value

A single numeric value.

Examples

# \donttest{
library(mlr3)
data(synth_train)
m <- s_learner(synth_train, outcome = "y", treatment = "t",
               learner = lrn("regr.rpart"))
ate(m, synth_train)
#> [1] 3.690471
# }