This package implements the causal KNN and treatment effect projection (TEP) heterogeneous treatment effect estimation algorithms introduced in Hitsch, Misra, and Zhang (2023).
To install this package in R, run the following commands in R:
install.packages("devtools") devtools::install_github("walterwzhang/causalKNN", build_vignettes = TRUE)
Alternatively, if you are installing the package from source, run the following commands in R:
install.packages(path_to_file, repos = NULL, type="source")
path_to_file is the local file path to the repository.
For how to use this package, please see the Intro Vignette or access it from R:
To bootstrap aggregate the estimators, please follow the Bootstrap Vignette:
knn.index.distfunction from the
glmnet) is offered as the treatment effect projection’s regression algorithm
Hitsch, Guenter J. and Misra, Sanjog and Zhang, Walter, Heterogeneous Treatment Effects and Optimal Targeting Policy Evaluation (February 28, 2023). Available at SSRN: https://ssrn.com/abstract=3111957 or http://dx.doi.org/10.2139/ssrn.3111957