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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: | 10.32614/CRAN.package.survcompare |
Author: | Diana Shamsutdinova
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Maintainer: | Diana Shamsutdinova <diana.shamsutdinova.github at gmail.com> |
License: | GPL (≥ 3) |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | survcompare results |
Reference manual: | survcompare.pdf |
Vignettes: |
survcompare_application |
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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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