Description Usage Arguments Value Author(s) References
Use random forest to adjust covariates and estimate average treatment effects and confidence intervals
1 | ate.randomForest(X, Y, W, nodesize = 20, conf.level = 0.9)
|
X |
Data matrix with covariates, one observation per row |
Y |
Outcome vector for assigned treatment for each observation |
W |
Treatment vector for each observation |
nodesize |
Node size for random forest. Default 20 |
conf.level |
Confidence level for intervals. Default 0.9 |
Returns list containing the following
tau |
Average treatment effect estimate |
var |
Variance estimate |
conf.int |
Confidence interval for true tau |
conf.level |
Confidence level |
Stefan Wager, Wenfei Du, Jonathan Taylor, Rob Tibshirani
S Wager, W Du, J Taylor, and R Tibshirani. "High-dimensional regression adjustments in randomized experiments". PNAS, November 8, 2016 vol. 113 no. 45 12673-12678
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