DualUplift {tools4uplift} | R Documentation |
Two-model estimator
Description
Fit the two-model uplift model estimator.
Usage
## S3 method for class 'formula'
DualUplift(formula, treat, data, ...)
## Default S3 method:
DualUplift(data, treat, outcome, predictors, ...)
Arguments
data , formula |
a data frame containing the treatment, the outcome and the predictors or a formula describing the model to be fitted. |
treat |
name of a binary (numeric) vector representing the treatment assignment (coded as 0/1). |
outcome |
name of a binary response (numeric) vector (coded as 0/1). |
predictors |
a vector of names representing the explanatory variables to include in the model. |
... |
additional arguments (other than |
Value
model0 |
Fitted model for control group |
model1 |
Fitted model for treatment group |
Author(s)
Mouloud Belbahri
References
Hansotia, B., J., and Rukstales B. (2001) Direct marketing for multichannel retailers: Issues, challenges and solutions. Journal of Database Marketing and Customer Strategy Management, Vol. 9(3), 259-266.
Belbahri, M., Murua, A., Gandouet, O., and Partovi Nia, V. (2019) Uplift Regression, <https://dms.umontreal.ca/~murua/research/UpliftRegression.pdf>
Examples
library(tools4uplift)
data("SimUplift")
fit <- DualUplift(SimUplift, "treat", "y", predictors = colnames(SimUplift[, 3:12]))
print(fit)
summary(fit)