Package: survcompare 0.3.0

Diana Shamsutdinova

survcompare: Nested Cross-Validation to Compare Cox-PH, Cox-Lasso, Survival Random Forests

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.

Authors:Diana Shamsutdinova [aut, cre], Daniel Stahl [aut]

survcompare_0.3.0.tar.gz
survcompare_0.3.0.tar.gz(r-4.7-any)survcompare_0.3.0.tar.gz(r-4.6-any)
survcompare_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
survcompare/json (API)

# Install 'survcompare' in R:

install.packages('survcompare', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.81 score 1 stars 13 scripts 310 downloads 20 exports 142 dependencies

Last updated from:db25ed2140. Checks:4 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	158
source / vignettes	OK	277
linux-release-x86_64	OK	182
wasm-release	OK	174

Exports:ml_hyperparams_srf simulate_crossterms simulate_linear simulate_nonlinear surv_validate survcompare survcompare2 survcox_cv survcox_predict survcox_train survcoxlasso_train survsrf_cv survsrf_predict survsrf_train survsrfens_cv survsrfens_predict survsrfens_train survsrfstack_cv survsrfstack_predict survsrfstack_train

Dependencies:backports base64enc bit bit64 bslib cachem caret checkmate class cli clipr clock cluster cmprsk codetools colorspace cpp11 crayon data.table data.tree diagram DiagrammeR digest doParallel dplyr e1071 evaluate farver fastmap fontawesome foreach foreign Formula fs future future.apply generics ggplot2 glmnet globals glue gower gridExtra gtable hardhat highr Hmisc hms htmlTable htmltools htmlwidgets igraph ipred isoband iterators jquerylib jsonlite KernSmooth knitr labeling lattice lava lifecycle listenv lubridate magrittr MASS Matrix MatrixModels memoise mets mime missForestPredict ModelMetrics multcomp mvtnorm nlme nnet numDeriv parallelly pec pillar pkgconfig plotrix plyr polspline prettyunits pROC prodlim progress progressr proxy Publish purrr quantreg R6 randomForestSRC ranger rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen readr recipes reshape2 riskRegression rlang rmarkdown rms rpart rstudioapi S7 sandwich sass scales shape SparseM sparsevctrs SQUAREM stringi stringr survival TH.data tibble tidyr tidyselect timechange timeDate timereg timeROC tinytex tzdb utf8 vctrs viridisLite visNetwork vroom withr xfun yaml zoo

Survcompare_application

Rendered fromsurvcompare_application.Rmdusingknitr::rmarkdown

Last update: 2025-06-25
Started: 2024-01-23

Help page	Topics
Auxiliary function for simulatedata functions	linear_beta
Internal function for getting grid of hyperparameters for random or grid search of size = max_grid_size	ml_hyperparams_srf
Print survcompare object	print.survcompare
Prints trained survensemble object	print.survensemble_cv
Simulated sample with survival outcomes with non-linear and cross-term dependencies	simulate_crossterms
Simulated sample with survival outcomes with linear dependencies	simulate_linear
Simulated sample with survival outcomes with non-linear dependencies	simulate_nonlinear
Summary of survcompare results	summary.survcompare
Prints summary of a trained survensemble_cv object	summary.survensemble_cv
Calculates time-dependent Brier Score	surv_brierscore
Computes performance statistics for a survival data given the predicted event probabilities	surv_validate
Cross-validates and compares Cox Proportionate Hazards and Survival Random Forest models	"_PACKAGE" survcompare
Compares two cross-validated models using surv____cv functions of this package.	survcompare2
Cross-validates Cox or CoxLasso model	survcox_cv
Computes event probabilities from a trained cox model	survcox_predict
Trains CoxPH using survival package, or trains CoxLasso (cv.glmnet, lambda.min), and then re-trains survival:coxph on non-zero predictors	survcox_train
Trains CoxLasso, using cv.glmnet(s="lambda.min")	survcoxlasso_train
Calculates survival probability estimated by Kaplan-Meier survival curve Uses polynomial extrapolation in survival function space, using poly(n=3)	survival_prob_km
Cross-validates Survival Random Forest	survsrf_cv
Predicts event probability by a trained Survival Random Forest	survsrf_predict
Fits randomForestSRC, with tuning by mtry, nodedepth, and nodesize. Underlying model is by Ishwaran et al(2008) https://www.randomforestsrc.org/articles/survival.html Ishwaran H, Kogalur UB, Blackstone EH, Lauer MS. Random survival forests. The Annals of Applied Statistics. 2008;2:841–60.	survsrf_train
A repeated 3-fold CV over a hyperparameters grid	survsrf_tune
Internal function for survsrf_tune(), performs 1 CV	survsrf_tune_single
Cross-validates predictive performance for SRF Ensemble	survsrfens_cv
Predicts event probability by a trained sequential ensemble of Survival Random Forest and CoxPH	survsrfens_predict
Fits an ensemble of Cox-PH and Survival Random Forest (SRF) with internal CV to tune SRF hyperparameters.	survsrfens_train
Cross-validates stacked ensemble of the CoxPH and Survival Random Forest models	survsrfstack_cv
Predicts event probability by a trained stacked ensemble of Survival Random Forest and CoxPH	survsrfstack_predict
Trains the stacked ensemble of the CoxPH and Survival Random Forest	survsrfstack_train

Package: survcompare 0.3.0

survcompare: Nested Cross-Validation to Compare Cox-PH, Cox-Lasso, Survival Random Forests

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