This package is in development. Improved documentation and examples coming soon.For questions, bugs, or feature additions, feel free to contact me at '[email protected]'!

The hte3 package equips users with tools for supervised causal machine learning of heterogeneous treatment effects, leveraging the sl3 package.

• Customizable Meta-learners of HTEs: Any supervised machine learning algorithm supported by the sl3 package can be turned into a meta-learner for heterogeneous treatment effects, including the DR-learner, R-learner, T-learner, and EP-learner of the CATE. For details on the usage of the sl3 R package, we refer to https://github.com/tlverse/sl3.

• Novel Meta-learners of the CRR: Implements novel EP-learners of the log conditional relative risk (CRR).

For comprehensive information, consult the package documentation.

To install the hte3 package, use the following command:

if(!require(devtools)) {
  install.packages("devtools")
}
devtools::install_github("Larsvanderlaan/hte3")