One major goal in clinical applications of time-to-event data is the estimation of survival with censored data. The usual nonparametric estimator of the survival function is the time-honored Kaplan-Meier product-limit estimator. Though this estimator has been implemented in several R packages, the development of the condSURV R package has been motivated by recent contributions that allow the estimation of the survival function for ordered multivariate failure time data. The condSURV package provides three different approaches all based on the Kaplan-Meier estimator. In one of these approaches these quantities are estimated conditionally on current or past covariate measures. Illustration of the software usage is included using real data.
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For attribution, please cite this work as
Meira-Machado & Sestelo, "condSURV: An R Package for the Estimation of the Conditional Survival Function for Ordered Multivariate Failure Time Data", The R Journal, 2017
BibTeX citation
@article{RJ-2016-059,
author = {Meira-Machado, Luis and Sestelo, Marta},
title = {condSURV: An R Package for the Estimation of the Conditional Survival Function for Ordered Multivariate Failure Time Data},
journal = {The R Journal},
year = {2017},
note = {https://doi.org/10.32614/RJ-2016-059},
doi = {10.32614/RJ-2016-059},
volume = {8},
issue = {2},
issn = {2073-4859},
pages = {460-473}
}