vt1_super: Estimate the CATE Using Super Learner for Step 1 of Virtual...

In tehtuner: Fit and Tune Models to Detect Treatment Effect Heterogeneity

Estimate the CATE Using Super Learner for Step 1 of Virtual Twins

Description

Estimate the CATE Using Super Learner for Step 1 of Virtual Twins

Usage

vt1_super(data, Trt, Y, SL.library, ...)

Arguments

data	a data frame containing a response, binary treatment indicators, and covariates.
Trt	a string specifying the name of the column of data contains the treatment indicators.
Y	a string specifying the name of the column of data contains the response.
SL.library	Either a character vector of prediction algorithms or a list containing character vector. See SuperLearner for more details.
...	additional arguments to SuperLearner

Value

Estimated CATEs for each subject in data.

See Also

Other VT Step 1 functions: vt1_lasso(), vt1_mars(), vt1_rf()

tehtuner documentation built on April 3, 2023, 5:16 p.m.