CondiS: Censored Data Imputation for Direct Modeling

Impute the survival times for censored observations based on their conditional survival distributions derived from the Kaplan-Meier estimator. 'CondiS' can replace the censored observations with the best approximations from the statistical model, allowing for direct application of machine learning-based methods. When covariates are available, 'CondiS' is extended by incorporating the covariate information through machine learning-based regression modeling ('CondiS_X'), which can further improve the imputed survival time.

Version: 0.1.1
Depends: R (≥ 3.6)
Imports: caret, survival, kernlab, purrr, tidyverse, survminer
Suggests: rmarkdown, knitr
Published: 2022-01-13
Author: Yizhuo Wang ORCID iD [aut, cre], Ziyi Li [aut], Xuelin Huang [aut], Christopher Flowers [ctb]
Maintainer: Yizhuo Wang <ywang70 at mdanderson.org>
License: GPL-2
NeedsCompilation: no
CRAN checks: CondiS results

Documentation:

Reference manual: CondiS.pdf
Vignettes: introduction

Downloads:

Package source: CondiS_0.1.1.tar.gz
Windows binaries: r-devel: CondiS_0.1.1.zip, r-release: CondiS_0.1.1.zip, r-oldrel: CondiS_0.1.1.zip
macOS binaries: r-release (arm64): CondiS_0.1.1.tgz, r-release (x86_64): CondiS_0.1.1.tgz, r-oldrel: not available

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