survcompare: Compares Cox and Survival Random Forests to Quantify Nonlinearity

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: 0.1.2
Depends: R (≥ 4.1), survival (≥ 3.0)
Imports: stats, timeROC, caret, glmnet, randomForestSRC
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-01-22
DOI: NA
Author: Diana Shamsutdinova ORCID iD [aut, cre], Daniel Stahl ORCID iD [aut]
Maintainer: Diana Shamsutdinova <diana.shamsutdinova.github at gmail.com>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README
CRAN checks: survcompare results

Documentation:

Reference manual: survcompare.pdf
Vignettes: survcompare_application

Downloads:

Package source: survcompare_0.1.2.tar.gz
Windows binaries: r-devel: survcompare_0.1.2.zip, r-release: survcompare_0.1.2.zip, r-oldrel: survcompare_0.1.2.zip
macOS binaries: r-release (arm64): survcompare_0.1.2.tgz, r-oldrel (arm64): survcompare_0.1.2.tgz, r-release (x86_64): survcompare_0.1.2.tgz, r-oldrel (x86_64): survcompare_0.1.2.tgz

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