Nested Cross-Validation to Compare Cox-PH, Cox-Lasso, Survival Random Forests R package survcompare version 0.3.0 Performs repeated nested cross-validation for Cox Proportionate Hazards, Cox Lasso, Survival Random Forest, and their ensemble. Returns internally validated concordance index, time-dependent area under the curve, Brier score, calibration slope, and statistical testing of non-linear ensemble outperforming the baseline Cox model. In this, it helps researchers to quantify the gain of using a more complex survival model, or justify its redundancy. Equally, it shows the performance value of the non-linear and interaction terms, and may highlight the need of further feature transformation. Further details can be found in Shamsutdinova, Stamate, Roberts, & Stahl (2022) "Combining Cox Model and Tree-Based Algorithms to Boost Performance and Preserve Interpretability for Health Outcomes" <doi:10.1007/978-3-031-08337-2_15>, where the method is described as Ensemble 1. Software Depends: R (>= 4.1), survival (>= 3.0) Imports: stats, timeROC, caret, glmnet, randomForestSRC, missForestPredict Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Diana Shamsutdinova <diana.shamsutdinova.github@gmail.com> Comprehensive R Archive Network (CRAN) Diana Shamsutdinova [aut, cre] (ORCID: <https://orcid.org/0000-0003-2434-3641>), Daniel Stahl [aut] (ORCID: <https://orcid.org/0000-0001-7987-6619>) GPL (>= 3) 2025-06-25 application/tgz https://CRAN.R-project.org/package=survcompare doi:10.32614/CRAN.package.survcompare