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:
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