A Survival Tree Based on Stabilized Score Tests for High-dimensional Covariates R package uni.survival.tree version 1.5 A classification (decision) tree is constructed from survival data with high-dimensional covariates. The method is a robust version of the logrank tree, where the variance is stabilized. The main function "uni.tree" returns a classification tree for a given survival dataset. The inner nodes (splitting criterion) are selected by minimizing the P-value of the two-sample the score tests. The decision of declaring terminal nodes (stopping criterion) is the P-value threshold given by an argument (specified by user). This tree construction algorithm is proposed by Emura et al. (2021, in review). Software Depends: survival,compound.Cox Takeshi Emura <takeshiemura@gmail.com> Comprehensive R Archive Network (CRAN) Takeshi Emura and Wei-Chern Hsu GPL-3 2021-03-22 application/tgz https://CRAN.R-project.org/package=uni.survival.tree doi:10.32614/CRAN.package.uni.survival.tree