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CERFIT: Causal Effect Random Forest of Interaction Tress
Fits a Causal Effect Random Forest of Interaction Tress (CERFIT) which is a modification of the Random Forest algorithm where each split is chosen to maximize subgroup treatment heterogeneity. Doing this allows it to estimate the individualized treatment effect for each observation in either randomized controlled trial (RCT) or observational data. For more information see X. Su, A. T. Peña, L. Liu, and R. A. Levine (2018) <doi:10.48550/arXiv.1709.04862>.
Getting started
Browse package contents
Package details |
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| Author | Justin Thorp [aut, cre], Luo Li [aut], Juanjuan Fan [aut] |
| Maintainer | Justin Thorp <jjtthorp@gmail.com> |
| License | GPL (>= 2) |
| Version | 0.1.0 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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Try the CERFIT package in your browser
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