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.
||R (≥ 3.6)
||caret, survival, kernlab, purrr, tidyverse, survminer
||Yizhuo Wang [aut,
Ziyi Li [aut],
Xuelin Huang [aut],
Christopher Flowers [ctb]
||Yizhuo Wang <ywang70 at mdanderson.org>
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