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 |
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