Package: survcomp 1.57.0

Benjamin Haibe-Kains

survcomp: Performance Assessment and Comparison for Survival Analysis

Assessment and Comparison for Performance of Risk Prediction (Survival) Models.

Authors:Benjamin Haibe-Kains [aut, cre], Markus Schroeder [aut], Catharina Olsen [aut], Christos Sotiriou [aut], Gianluca Bontempi [aut], John Quackenbush [aut], Samuel Branders [aut], Zhaleh Safikhani [aut]

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# Install 'survcomp' in R:
install.packages('survcomp', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • mainz7g - Subset of MAINZ dataset containing gene expression, annotations and clinical data.
  • nki7g - Subset of NKI dataset containing gene expression, annotations and clinical data.
  • transbig7g - Subset of the TRANSBIG dataset containing gene expression, annotations and clinical data.
  • unt7g - Subset of UNT dataset containing gene expression, annotations and clinical data.
  • upp7g - Subset of UPP dataset containing gene expression, annotations and clinical data.
  • vdx7g - Subset of VDX dataset containing gene expression, annotations and clinical data.

On BioConductor:survcomp-1.57.0(bioc 3.21)survcomp-1.56.0(bioc 3.20)

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

geneexpressiondifferentialexpressionvisualization

8.45 score 12 packages 444 scripts 1.8k downloads 117 mentions 37 exports 30 dependencies

Last updated 23 days agofrom:d938b84f9a. Checks:OK: 3 NOTE: 2 WARNING: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 18 2024
R-4.5-win-x86_64NOTENov 18 2024
R-4.5-linux-x86_64NOTENov 18 2024
R-4.4-win-x86_64OKNov 18 2024
R-4.4-mac-x86_64WARNINGNov 18 2024
R-4.4-mac-aarch64WARNINGNov 18 2024
R-4.3-win-x86_64OKNov 18 2024
R-4.3-mac-x86_64WARNINGNov 18 2024
R-4.3-mac-aarch64WARNINGNov 18 2024

Exports:balanced.hazard.ratiobhr.compcensor.timecindex.compcindex.comp.metacombine.estcombine.testconcordance.indexconcordanceIndexCcvplD.indexdindex.compdindex.comp.metafisherzforestplot.survget_concordanceIndex_onevariablegetsurv2hazard.ratiohr.comphr.comp.metahr.comp2iauc.compibsc.compkm.coxph.plotlogplmetaplot.survmrmr_cIndexmrmr_cIndex_ensemble_removemrmr.cindexmrmr.cindex.ensembleno.at.risksbrier.score2probascore2probatd.sens.spectdrocctest.hetero.esttest.hetero.test

Dependencies:bootstrapclassclicodetoolsdata.tablediagramdigestfuturefuture.applyglobalsipredKernSmoothlatticelavalistenvMASSMatrixnnetnumDerivparallellyprodlimprogressrRcpprmetarpartshapeSQUAREMSuppDistssurvivalsurvivalROC

SurvComp: a package for performance assessment and comparison for survival analysis

Rendered fromsurvcomp.Rnwusingutils::Sweaveon Nov 18 2024.

Last update: 2020-01-31
Started: 2014-08-20

Readme and manuals

Help Manual

Help pageTopics
Performance Assessment and Comparison for Survival Analysissurvcomp-package survcomp
Function to estimate the balanced hazard ratio through Cox regressionbalanced.hazard.ratio
Function to statistically compare two balanced hazard ratiosbhr.comp
Sample data containing six datasets for gene expression, annotations and clinical data.breastCancerData
Function to artificially censor survival datacensor.time
Function to compare two concordance indicescindex.comp
Function to compare two concordance indicescindex.comp.meta
Function to combine estimatescombine.est
Function to combine probabilitiescombine.test
Function to compute the concordance index for survival or binary class predictionconcordance.index
Concordance index CconcordanceIndexC
Function to compute the CVPLcvpl
Function to compute the D indexD.index
Function to compare two D indicesdindex.comp
Function to compare two D indicesdindex.comp.meta
Function to compute Fisher z transformationfisherz
Forest plots enables to display performance estimates of survival modelsforestplot.surv
Get concordance indexget_concordanceIndex_onevariable
Function to retrieve the survival probabilities at a specific point in timegetsurv2
Function to estimate the hazard ratio through Cox regressionhazard.ratio
Function to statistically compare two hazard ratioshr.comp
Function to compare two concordance indiceshr.comp.meta
Function to statistically compare two hazard ratios (alternative interface)hr.comp2
Function to compare two IAUCs through time-dependent ROC curvesiauc.comp
Function to compare two IBSCsibsc.comp
Function to plot several Kaplan-Meier survival curveskm.coxph.plot
Function to compute the log partial likelihood of a Cox modellogpl
Subset of MAINZ dataset containing gene expression, annotations and clinical data.mainz7g
Meta-analysis plot (forest plot)metaplot.surv
mRMR cIndexmrmr_cIndex
mRMR cIndex Ensemble Removemrmr_cIndex_ensemble_remove
Function to compute the concordance index for survival or binary class predictionmrmr.cindex
Function to compute the concordance index for survival or binary class predictionmrmr.cindex.ensemble
Subset of NKI dataset containing gene expression, annotations and clinical data.nki7g
Function to compute the number of individuals at riskno.at.risk
Function to compute the BSCs from a risk score, for all the times of event occurrencesbrier.score2proba
Function to compute the survival probabilities from a risk scorescore2proba
Function to compute sensitivity and specificity for a binary classification of survival datatd.sens.spec
Function to compute time-dependent ROC curvestdrocc
Function to test the heterogeneity of set of probabilitiestest.hetero.est
Function to test the heterogeneity of set of probabilitiestest.hetero.test
Subset of the TRANSBIG dataset containing gene expression, annotations and clinical data.transbig7g
Subset of UNT dataset containing gene expression, annotations and clinical data.unt7g
Subset of UPP dataset containing gene expression, annotations and clinical data.upp7g
Subset of VDX dataset containing gene expression, annotations and clinical data.vdx7g