dipm: Depth Importance in Precision Medicine (DIPM) Method
An implementation by Chen, Li, and Zhang (2022) <doi:10.1093/bioadv/vbac041> of the Depth Importance in Precision Medicine (DIPM) method
in Chen and Zhang (2022) <doi:10.1093/biostatistics/kxaa021> and Chen and
Zhang (2020) <doi:10.1007/978-3-030-46161-4_16>. The DIPM method is a classification
tree that searches for subgroups with especially poor or strong performance in a given treatment group.
| Version: |
1.8 |
| Depends: |
R (≥ 3.0.0) |
| Imports: |
stats, utils, survival, partykit (≥ 1.2-6), ggplot2, grid |
| Published: |
2022-07-14 |
| Author: |
Cai Li [aut, cre],
Victoria Chen [aut],
Heping Zhang [aut] |
| Maintainer: |
Cai Li <cai.li.stats at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| In views: |
MachineLearning |
| CRAN checks: |
dipm results |
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