Receiver Operating Characteristic (ROC)guided survival trees and forests algorithms are implemented, providing a unified framework for treestructured analysis with censored survival outcomes. A timeinvariant partition scheme on the survivor population was considered to incorporate timedependent covariates. Motivated by ideas of randomized tests, generalized timedependent ROC curves were used to evaluate the performance of survival trees and establish the optimality of the target hazard function. The optimality of the target hazard function motivates us to use a weighted average of the timedependent area under the curve (AUC) on a set of time points to evaluate the prediction performance of survival trees and to guide splitting and pruning. A detailed description of the implemented methods can be found in Sun et al. (2019) <arXiv:1809.05627>.
Package details 


Author  Yifei Sun [aut], MeiCheng Wang [aut], Sy Han Chiou [aut, cre] 
Maintainer  Sy Han Chiou <[email protected]> 
License  GPL (>= 3) 
Version  1.0.0 
URL  http://github.com/stc04003/rocTree 
Package repository  View on CRAN 
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