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: |
0.1.2 |
| Depends: |
R (≥ 3.6) |
| Imports: |
caret, survival, kernlab, purrr, tidyverse, survminer |
| Suggests: |
rmarkdown, knitr |
| Published: |
2022-04-17 |
| DOI: |
10.32614/CRAN.package.CondiS |
| Author: |
Yizhuo Wang  [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:
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