View source: R/ce_estimate_tmle_ate.R
ce_estimate_tmle_ate | R Documentation |
The function ce_estimate_tmle_ate
implements
TMLE to estimate ATE effect with
multiple treatments using observational data.
ce_estimate_tmle_ate(y, w, x, sl_library, ...)
y |
A numeric vector (0, 1) representing a binary outcome. |
w |
A numeric vector representing the treatment groups. |
x |
A dataframe, including all the covariates but not treatments. |
sl_library |
A character vector of prediction algorithms.
A list of functions included in the SuperLearner package
can be found with |
... |
Other parameters that can be passed through to functions. |
A summary of the effect estimates can be obtained
with summary
function.
Hadley Wickham, Romain François, Lionel Henry and Kirill Müller (2021). dplyr: A Grammar of Data Manipulation. R package version 1.0.7. URL: https://CRAN.R-project.org/package=dplyr
Eric Polley, Erin LeDell, Chris Kennedy and Mark van der Laan (2021). SuperLearner: Super Learner Prediction. R package version 2.0-28. URL:https://CRAN.R-project.org/package=SuperLearner
Susan Gruber, Mark J. van der Laan (2012). tmle: An R Package for Targeted Maximum Likelihood Estimation. Journal of Statistical Software, 51(13), 1-35.
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