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: 1.11 Depends: R (≥ 3.0.0) Imports: stats, utils, survival, partykit (≥ 1.2-6), ggplot2, grid Published: 2025-06-16 DOI: 10.32614/CRAN.package.dipm 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 Documentation: Reference manual: dipm.html , dipm.pdf Downloads: Package source: dipm_1.11.tar.gz Windows binaries: r-devel: dipm_1.11.zip, r-release: dipm_1.11.zip, r-oldrel: dipm_1.11.zip macOS binaries: r-release (arm64): dipm_1.11.tgz, r-oldrel (arm64): dipm_1.11.tgz, r-release (x86_64): dipm_1.11.tgz, r-oldrel (x86_64): dipm_1.11.tgz Old sources: dipm archive Linking:Please use the canonical form https://CRAN.R-project.org/package=dipm to link to this page.
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