Package: caROC 0.1.5

caROC: Continuous Biomarker Evaluation with Adjustment of Covariates

Compute covariate-adjusted specificity at controlled sensitivity level, or covariate-adjusted sensitivity at controlled specificity level, or covariate-adjust receiver operating characteristic curve, or covariate-adjusted thresholds at controlled sensitivity/specificity level. All statistics could also be computed for specific sub-populations given their covariate values. Methods are described in Ziyi Li, Yijian Huang, Datta Patil, Martin G. Sanda (2021+) "Covariate adjustment in continuous biomarker assessment".

Authors:Ziyi Li

caROC_0.1.5.tar.gz
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caROC.pdf |caROC.html✨
caROC/json (API)

# Install 'caROC' in R:
install.packages('caROC', repos = c('https://ziyili20.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 5 scripts 170 downloads 9 exports 8 dependencies

Last updated 4 years agofrom:6c243aa38c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-winOKNov 06 2024
R-4.5-linuxOKNov 06 2024
R-4.4-winOKNov 06 2024
R-4.4-macOKNov 06 2024
R-4.3-winOKNov 06 2024
R-4.3-macOKNov 06 2024

Exports:caROCcaROC_CBcaThresholdplot_caROCplot_caROC_CBplot_sscaROCplot_sscaROC_CBsscaROCsscaROC_CB

Dependencies:latticeMASSMatrixMatrixModelsquantregRColorBrewerSparseMsurvival

Evaluate continuous biomarkers with caROC

Ziyi Li ([email protected])

Rendered fromcaROC.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2021-04-02
Started: 2021-04-02