Package: dipm
Title: Depth Importance in Precision Medicine (DIPM) Method
Version: 1.11
Date: 2025-06-15
Authors@R: c(person(given = "Cai", family = "Li", 
	             role = c("aut", "cre"), email = "cai.li.stats@gmail.com"),
             person(given = "Victoria", family = "Chen", 
                    role = "aut", email = "victoria.chen@yale.edu"),
             person(given = "Heping", family = "Zhang", 
                    role = "aut", email = "heping.zhang@yale.edu"))
Maintainer: Cai Li <cai.li.stats@gmail.com>
Description: 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.
Depends: R (>= 3.0.0)
Imports: stats, utils, survival, partykit (>= 1.2-6), ggplot2, grid
NeedsCompilation: yes
License: GPL (>= 2)
Encoding: UTF-8
LazyLoad: yes
Repository: CRAN
RoxygenNote: 7.3.2
Packaged: 2025-06-15 23:58:31 UTC; cli9
Author: Cai Li [aut, cre],
  Victoria Chen [aut],
  Heping Zhang [aut]
Date/Publication: 2025-06-16 02:10:02 UTC
Built: R 4.3.3; x86_64-apple-darwin20; 2025-06-19 04:56:35 UTC; unix
Archs: dipm.so.dSYM
