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.
Version: 0.3.0 Depends: R (≥ 4.1), survival (≥ 3.0) Imports: stats, timeROC, caret, glmnet, randomForestSRC, missForestPredict Suggests: knitr, rmarkdown, testthat (≥ 3.0.0) Published: 2025-06-25 DOI: 10.32614/CRAN.package.survcompare Author: Diana Shamsutdinova [aut, cre], Daniel Stahl [aut] Maintainer: Diana Shamsutdinova <diana.shamsutdinova.github at gmail.com> License: GPL (≥ 3) NeedsCompilation: no Materials: README CRAN checks: survcompare results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=survcompare to link to this page.
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