htetree: Causal Inference with Tree-Based Machine Learning Algorithms

Estimating heterogeneous treatment effects with tree-based machine learning algorithms and visualizing estimated results in flexible and presentation-ready ways. For more information, see Brand, Xu, Koch, and Geraldo (2021) <doi:10.1177/0081175021993503>. Our current package first started as a fork of the 'causalTree' package on 'GitHub' and we greatly appreciate the authors for their extremely useful and free package.

Version: 0.1.18
Depends: R (≥ 3.6.0)
Imports: Rcpp, grf, partykit, data.tree, Matching, dplyr, jsonlite, rpart, rpart.plot, shiny, stringr
Suggests: optmatch, haven, foreign, data.table, remotes, party
Published: 2023-11-29
Author: Jiahui Xu [cre, aut], Tanvi Shinkre [aut], Jennie Brand [aut]
Maintainer: Jiahui Xu <jiahuixu at ucla.edu>
License: GPL-2 | GPL-3
NeedsCompilation: yes
CRAN checks: htetree results

Documentation:

Reference manual: htetree.pdf

Downloads:

Package source: htetree_0.1.18.tar.gz
Windows binaries: r-devel: htetree_0.1.18.zip, r-release: htetree_0.1.18.zip, r-oldrel: htetree_0.1.18.zip
macOS binaries: r-release (arm64): htetree_0.1.18.tgz, r-oldrel (arm64): htetree_0.1.18.tgz, r-release (x86_64): htetree_0.1.18.tgz
Old sources: htetree archive

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