Receiver Operating Characteristic (ROC)-guided survival trees and ensemble algorithms are implemented, providing a unified framework for tree-structured analysis with censored survival outcomes. A time-invariant partition scheme on the survivor population was considered to incorporate time-dependent covariates. Motivated by ideas of randomized tests, generalized time-dependent ROC curves were used to evaluate the performance of survival trees and establish the optimality of the target hazard/survival function. The optimality of the target hazard function motivates us to use a weighted average of the time-dependent 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 |
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Author | Yifei Sun [aut], Mei-Cheng Wang [aut], Sy Han Chiou [aut, cre] |
Maintainer | Sy Han Chiou <schiou@utdallas.edu> |
License | GPL (>= 3) |
Version | 1.1.1 |
URL | http://github.com/stc04003/rocTree |
Package repository | View on CRAN |
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