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.


Reference manual

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0.1.1 by Yizhuo Wang, 6 days ago

Browse source code at https://github.com/cran/CondiS

Authors: Yizhuo Wang [aut, cre] , Ziyi Li [aut] , Xuelin Huang [aut] , Christopher Flowers [ctb]

Documentation:   PDF Manual  

GPL-2 license

Imports caret, survival, kernlab, purrr, tidyverse, survminer

Suggests rmarkdown, knitr

See at CRAN