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) . 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.


Reference manual

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install.packages("htetree")

0.1.23 by Jiahui Xu, 7 months ago


Browse source code at https://github.com/cran/htetree


Authors: Jiahui Xu [cre, aut] , Tanvi Shinkre [aut] , Jennie Brand [aut]


Documentation:   PDF Manual  


GPL-2 | GPL-3 license


Imports Rcpp, grf, partykit, data.tree, Matching, dplyr, jsonlite, rpart, rpart.plot, shiny, stringr

Suggests optmatch, haven, foreign, data.table, remotes, party


See at CRAN