Package: CSTE
Version: 3.0.0
Date: 2024-11-16
Type: Package
Title: Covariate Specific Treatment Effect (CSTE) Curve
Description: A uniform  statistical inferential tool in making individualized treatment decisions, which implements the methods of Ma et al. (2017)<DOI:10.1177/0962280214541724> 
    and Guo et al. (2021)<DOI:10.1080/01621459.2020.1865167>. It uses a flexible semiparametric modeling strategy for heterogeneous treatment effect estimation in high-dimensional settings and can gave valid confidence bands. Based on it, one can find the subgroups of patients that benefit from each treatment, thereby making individualized treatment selection.
Authors@R: c(
  person("Peng", "Wu", email = "wupeng@bicmr.pku.edu.cn", role = "aut"),
  person("Wenjie", "Hu", email = "huwenjie@pku.edu.cn", role = c("aut", "cre")),
  person("Yuhao", "Deng", email = "dengyuhao@pku.edu.cn", role = "aut"),
  person("Haoxiang", "Wang", email = "whxwhx@pku.edu.cn", role = "aut"),
  person("Xiaohua", "Zhou", email = "azhou@math.pku.edu.cn", role = "aut"))
License: GPL (>= 2)
Encoding: UTF-8
Imports: Rcpp (>= 1.0.4), fda, splines, survival, locpol, dfoptim
LinkingTo: Rcpp
RoxygenNote: 7.1.1
Suggests: mvtnorm, sigmoid
NeedsCompilation: yes
Packaged: 2024-11-18 16:47:21 UTC; wenjiehu
Author: Peng Wu [aut],
  Wenjie Hu [aut, cre],
  Yuhao Deng [aut],
  Haoxiang Wang [aut],
  Xiaohua Zhou [aut]
Maintainer: Wenjie Hu <huwenjie@pku.edu.cn>
Repository: CRAN
Date/Publication: 2024-11-19 12:00:15 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-25 12:52:46 UTC; unix
Archs: CSTE.so.dSYM
