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Personalized assignment to one of many treatment arms via regularized and clustered joint assignment forests as described in Ladhania, Spiess, Ungar, and Wu (2023) <doi:10.48550/arXiv.2311.00577>. The algorithm pools information across treatment arms: it considers a regularized forest-based assignment algorithm based on greedy recursive partitioning that shrinks effect estimates across arms; and it incorporates a clustering scheme that combines treatment arms with consistently similar outcomes.
Package details |
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Author | Wenbo Wu [aut, cph] (<https://orcid.org/0000-0002-7642-9773>), Xinyi Zhang [aut, cre, cph] (<https://orcid.org/0009-0007-7306-491X>), Jann Spiess [aut, cph] (<https://orcid.org/0000-0002-4120-8241>), Rahul Ladhania [aut, cph] (<https://orcid.org/0000-0002-7902-7681>) |
Maintainer | Xinyi Zhang <zhang.xinyi@nyu.edu> |
License | GPL-3 |
Version | 0.1.3 |
URL | https://github.com/wustat/rjaf |
Package repository | View on CRAN |
Installation |
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