Package: CSTE 3.0.0
CSTE: Covariate Specific Treatment Effect (CSTE) Curve
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:
CSTE_3.0.0.tar.gz
CSTE_3.0.0.zip(r-4.7)CSTE_3.0.0.zip(r-4.6)CSTE_3.0.0.zip(r-4.5)
CSTE_3.0.0.tgz(r-4.6-x86_64)CSTE_3.0.0.tgz(r-4.6-arm64)CSTE_3.0.0.tgz(r-4.5-x86_64)CSTE_3.0.0.tgz(r-4.5-arm64)
CSTE_3.0.0.tar.gz(r-4.7-arm64)CSTE_3.0.0.tar.gz(r-4.7-x86_64)CSTE_3.0.0.tar.gz(r-4.6-arm64)CSTE_3.0.0.tar.gz(r-4.6-x86_64)
CSTE_3.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
CSTE/json (API)
| # Install 'CSTE' in R: |
| install.packages('CSTE', repos = c('https://hwj0828.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:a2329d6325. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 131 | ||
| linux-devel-x86_64 | OK | 146 | ||
| source / vignettes | OK | 407 | ||
| linux-release-arm64 | OK | 130 | ||
| linux-release-x86_64 | OK | 145 | ||
| macos-release-arm64 | OK | 230 | ||
| macos-release-x86_64 | OK | 207 | ||
| macos-oldrel-arm64 | OK | 186 | ||
| macos-oldrel-x86_64 | OK | 256 | ||
| windows-devel | OK | 117 | ||
| windows-release | OK | 134 | ||
| windows-oldrel | OK | 108 | ||
| wasm-release | OK | 112 |
Exports:cntcovcste_bincste_bin_SCBcste_survcste_surv_SCBgget.boundgetthreslogitinvlplmy_logitmy_survnormalizepenCpredict_cste_binprev_fit_cstepupu_invsampleQselect_cste_binztrans
Dependencies:ashbitopscliclustercolorspacecpp11deSolvedfoptimfarverfdafdsFNNggplot2gluegtablehdrcdeisobandkernlabKernSmoothkslabelinglatticelifecyclelocfitlocpolMASSMatrixmclustmgcvmulticoolmvtnormnlmepcaPPpracmaR6rainbowRColorBrewerRcppRCurlrlangS7scalessurvivalvctrsviridisLitewithr
