Estimation of the Average Treatment Effect among Responders
RATE( response, post.treatment, treatment, data, family = gaussian(), M = 5, pr.treatment, treatment.level, SL.args.response = list(family = gaussian(), SL.library = c("SL.mean", "SL.glm")), SL.args.post.treatment = list(family = binomial(), SL.library = c("SL.mean", "SL.glm")), preprocess = NULL, efficient = TRUE, ... )
Response formula (e.g, Y~D*A)
Post treatment marker formula (e.g., D~W)
Treatment formula (e.g, A~1)
Exponential family for response (default gaussian)
Number of folds in cross-fitting (M=1 is no cross-fitting)
(optional) Randomization probability of treatment.
Treatment level in binary treatment (default 1)
Arguments to SuperLearner for the response model
Arguments to SuperLearner for the post treatment indicator
(optional) Data preprocessing function
If TRUE, the estimate will be efficient. If FALSE, the estimate will be a simple plug-in estimate.
Additional arguments to lower level functions