Package: riskRegression 2023.12.21

Thomas Alexander Gerds

riskRegression: Risk Regression Models and Prediction Scores for Survival Analysis with Competing Risks

Implementation of the following methods for event history analysis. Risk regression models for survival endpoints also in the presence of competing risks are fitted using binomial regression based on a time sequence of binary event status variables. A formula interface for the Fine-Gray regression model and an interface for the combination of cause-specific Cox regression models. A toolbox for assessing and comparing performance of risk predictions (risk markers and risk prediction models). Prediction performance is measured by the Brier score and the area under the ROC curve for binary possibly time-dependent outcome. Inverse probability of censoring weighting and pseudo values are used to deal with right censored data. Lists of risk markers and lists of risk models are assessed simultaneously. Cross-validation repeatedly splits the data, trains the risk prediction models on one part of each split and then summarizes and compares the performance across splits.

Authors:Thomas Alexander Gerds [aut, cre], Johan Sebastian Ohlendorff [aut], Paul Blanche [ctb], Rikke Mortensen [ctb], Marvin Wright [ctb], Nikolaj Tollenaar [ctb], John Muschelli [ctb], Ulla Brasch Mogensen [ctb], Brice Ozenne [aut]

riskRegression_2023.12.21.tar.gz
riskRegression_2023.12.21.tar.gz(r-4.5-noble)riskRegression_2023.12.21.tar.gz(r-4.4-noble)
riskRegression_2023.12.21.tgz(r-4.4-emscripten)
riskRegression.pdf |riskRegression.html
riskRegression/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/tagteam/riskregression/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

8.50 score 1 stars 32 packages 708 scripts 9.3k downloads 27 mentions 71 exports 102 dependencies

Last updated 12 months agofrom:1cddb04295. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 14 2024
R-4.5-linux-x86_64NOTENov 14 2024

Exports:ARRatebaseHaz_cppboot2pvalueCforestcolCenter_cppcolCumSumcolMultiply_cppcolScale_cppcoxBaseEstimatorcoxCentercoxFormulacoxLPcoxModelFramecoxNcoxSpecialcoxStratacoxStrataLevelcoxVarCovcoxVariableNameCSCCtreediscreteRootFGRgetSplitMethodGLMnetHal9001iidCoxinfluenceTestIPAipcwLRRpenalizedS3plotAUCplotBrierplotCalibrationplotEffectsplotPredictRiskplotRiskplotROCpredictCoxpredictCoxPLpredictRiskriskLevelPlotriskRegressionriskRegression.optionsrowCenter_cpprowCumSumrowMultiply_cpprowScale_cpprowSumsCrossprodrsquaredsampleDatasampleDataTDsaveCoxConfidentialScoreScore.listselectCoxsimActiveSurveillancesimMelanomasimPBCsimsynthsubjectWeightssubsetIndexsummary.ScoreSuperPredictorsynthesizesynthesize.formulasynthesize.lvmtransformCIBPwglm

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercmprskcodetoolscolorspacedata.tablediagramdigestdoParallelevaluatefansifarverfastmapfontawesomeforeachforeignFormulafsfuturefuture.applyggplot2globalsgluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvmagrittrMASSMatrixMatrixModelsmemoisemetsmgcvmimemultcompmunsellmvtnormnlmennetnumDerivparallellypillarpkgconfigplotrixpolsplineprodlimprogressrPublishquantregR6rangerrappdirsRColorBrewerRcppRcppArmadilloRcppEigenrlangrmarkdownrmsrpartrstudioapisandwichsassscalesshapeSparseMSQUAREMstringistringrsurvivalTH.datatibbletimeregtinytexutf8vctrsviridisviridisLitewithrxfunyamlzoo

IPA: Index of Prediction Accuracy

Rendered fromIPA.html.asisusingR.rsp::asison Nov 14 2024.

Last update: 2019-11-04
Started: 2019-11-04

Readme and manuals

Help Manual

Help pageTopics
Risk Comparison Over Timeanova.ate
Turn ate Object Into a 'data.table'as.data.table.ate
Turn influenceTest Object Into a 'data.table'as.data.table.influenceTest
Turn predictCox Object Into a 'data.table'as.data.table.predictCox
Turn predictCSC Object Into a 'data.table'as.data.table.predictCSC
Average Treatment Effects Computationate
Plot Average Risksautoplot.ate
Plot Predictions From a Cox Modelautoplot.predictCox
Plot Predictions From a Cause-specific Cox Proportional Hazard Regressionautoplot.predictCSC
ggplot AUC curveautoplot.Score
C++ Fast Baseline Hazard EstimationbaseHaz_cpp
Compute the p.value from the distribution under H1boot2pvalue
Boxplot risk quantilesboxplot.Score
Computation of standard errors for predictionscalcSeCox
Standard error of the absolute risk predicted from cause-specific Cox modelscalcSeCSC
S3-wrapper function for cforest from the party packageCforest
Extract coefficients from a Cause-Specific Cox regression modelcoef.CauseSpecificCox
Extract coefficients from riskRegression modelcoef.riskRegression
Apply - by columncolCenter_cpp
Apply cumsum in each columncolCumSum
Apply * by columncolMultiply_cpp
Apply / by columncolScale_cpp
Confidence Intervals and Confidence Bands for the Predicted Absolute Risk (Cumulative Incidence Function)confint.ate
Confidence Intervals and Confidence Bands for the Difference Between Two Estimatesconfint.influenceTest
Confidence Intervals and Confidence Bands for the predicted Survival/Cumulative Hazardconfint.predictCox
Confidence Intervals and Confidence Bands for the Predicted Absolute Risk (Cumulative Incidence Function)confint.predictCSC
Extract the type of estimator for the baseline hazardcoxBaseEstimator coxBaseEstimator.coxph coxBaseEstimator.phreg
Extract the mean value of the covariatescoxCenter coxCenter.coxph coxCenter.cph coxCenter.phreg
Extract the formula from a Cox modelcoxFormula coxFormula.coxph coxFormula.cph coxFormula.glm coxFormula.phreg
Compute the linear predictor of a Cox modelcoxLP coxLP.coxph coxLP.cph coxLP.phreg
Extract the design matrix used to train a Cox modelcoxModelFrame coxModelFrame.coxph coxModelFrame.cph coxModelFrame.phreg
Extract the number of observations from a Cox modelcoxN coxN.CauseSpecificCox coxN.coxph coxN.cph coxN.glm coxN.phreg
Special characters in Cox modelcoxSpecial coxSpecial.coxph coxSpecial.cph coxSpecial.phreg
Define the strata for a new datasetcoxStrata coxStrata.coxph coxStrata.cph coxStrata.phreg
Returns the name of the strata in Cox modelcoxStrataLevel coxStrataLevel.coxph coxStrataLevel.cph coxStrataLevel.phreg
Extract the variance covariance matrix of the beta from a Cox modelcoxVarCov coxVarCov.coxph coxVarCov.cph coxVarCov.phreg
Extract variable names from a modelcoxVariableName
Cause-specific Cox proportional hazard regressionCSC
S3-Wrapper for ctree.Ctree
Dichotomic search for monotone functiondiscreteRoot
Formula wrapper for crr from cmprskFGR
Input for data splitting algorithmsgetSplitMethod
Fitting GLMnet for use with predictRiskGLMnet
Fitting HAL for use with predictRiskHal9001
IID for IPCW Logistic Regressionsiid.wglm
Extract iid decomposition from a Cox modeliidCox iidCox.CauseSpecificCox iidCox.coxph iidCox.cph iidCox.phreg
Influence test [Experimental!!]influenceTest influenceTest.default influenceTest.list
Information for IPCW Logistic Regressionsinformation.wglm
Explained variation for settings with binary, survival and competing risk outcomeIPA IPA.CauseSpecificCox IPA.coxph IPA.default IPA.glm rsquared rsquared.CauseSpecificCox rsquared.coxph rsquared.default rsquared.glm
Estimation of censoring probabilitiesipcw ipcw.aalen ipcw.cox ipcw.marginal ipcw.none ipcw.nonpar
Malignant melanoma dataMelanoma
Extract design matrix for cph objectsmodel.matrix.cph
Extract design matrix for phreg objectsmodel.matrix.phreg
Paquid samplePaquid
S3-wrapper for S4 function penalizedpenalizedS3
Plotting predicted riskplot.riskRegression
Plot of time-dependent AUC curvesplotAUC
Plot Brier curveplotBrier
Plot Calibration curveplotCalibration
Plotting time-varying effects from a risk regression model.plotEffects
Plotting predicted risks curves.plotPredictRisk
plot predicted risksplotRisk
Plot ROC curvesplotROC
Predicting Absolute Risk from Cause-Specific Cox Modelspredict.CauseSpecificCox predictBig.CauseSpecificCox
Predict subject specific risks (cumulative incidence) based on Fine-Gray regression modelpredict.FGR
Predict individual risk.predict.riskRegression
Fast computation of survival probabilities, hazards and cumulative hazards from Cox regression modelspredictCox
Computation of survival probabilities from Cox regression models using the product limit estimator.predictCoxPL
Extrating predicting risks from regression modelspredictRisk predictRisk.aalen predictRisk.ARR predictRisk.BinaryTree predictRisk.CauseSpecificCox predictRisk.comprisk predictRisk.cox.aalen predictRisk.CoxConfidential predictRisk.coxph predictRisk.coxph.penal predictRisk.coxphTD predictRisk.cph predictRisk.CSCTD predictRisk.default predictRisk.double predictRisk.factor predictRisk.FGR predictRisk.flexsurvreg predictRisk.formula predictRisk.gbm predictRisk.glm predictRisk.GLMnet predictRisk.Hal9001 predictRisk.integer predictRisk.lrm predictRisk.matrix predictRisk.multinom predictRisk.numeric predictRisk.pecCforest predictRisk.pecCtree predictRisk.penfitS3 predictRisk.prodlim predictRisk.psm predictRisk.randomForest predictRisk.ranger predictRisk.rfsrc predictRisk.riskRegression predictRisk.rpart predictRisk.selectCox predictRisk.singleEventCB predictRisk.SuperPredictor predictRisk.survfit predictRisk.wglm
Print Average Treatment Effectsprint.ate
Print of a Cause-Specific Cox regression modelprint.CauseSpecificCox
Print of a Fine-Gray regression modelprint.FGR
Output of the DIfference Between Two Estimatesprint.influenceTest
Print IPA objectprint.IPA
Print Predictions From a Cox Modelprint.predictCox
Print Predictions From a Cause-specific Cox Proportional Hazard Regressionprint.predictCSC
Print function for riskRegression modelsprint.riskRegression
Print Score objectprint.Score
Print subject weightsprint.subjectWeights
Reconstruct the original datasetreconstructData
Level plots for risk prediction modelsriskLevelPlot
Risk Regression Fits a regression model for the risk of an event - allowing for competing risks.ARR LRR riskRegression
Global options for 'riskRegression'riskRegression.options
Apply - by rowrowCenter_cpp
Apply cumsum in each rowrowCumSum
Apply * by rowrowMultiply_cpp
Collapse Rows of Characters.rowPaste
Apply / by rowrowScale_cpp
Apply crossprod and rowSumsrowSumsCrossprod
Simulate data with binary or time-to-event outcomesampleData sampleDataTD
Save confidential Cox objectssaveCoxConfidential
Score risk predictionsScore Score.list
Score for IPCW Logistic Regressionsscore.wglm
Backward variable selection in the Cox regression modelselectCox
Evaluate the influence function at selected timesselectJump
Simulate data of a hypothetical active surveillance prostate cancer studysimActiveSurveillance
Simulate data alike the Melanoma datasimMelanoma
simulating data alike the pbc datasimPBC
Simulating from a synthesized objectsimsynth
SmcFcsSmcFcs
Reconstruct each of the strata variablessplitStrataVar
Estimation of censoring probabilities at subject specific timessubjectWeights subjectWeights.aalen subjectWeights.cox subjectWeights.km subjectWeights.marginal subjectWeights.none subjectWeights.nonpar
Extract Specific Elements From An ObjectsubsetIndex subsetIndex.default subsetIndex.matrix
Summary Average Treatment Effectssummary.ate
Summary of a Fine-Gray regression modelsummary.FGR
Summary of a risk regression modelsummary.riskRegression
Summary of prediction performance metricssummary.Score
Formula interface for SuperLearner::SuperLearnerSuperPredictor
Extract the time and event variable from a Cox modelSurvResponseVar
Cooking and synthesizing survival datasynthesize synthesize.formula synthesize.lvm
Extract terms for phreg objectsterms.phreg
Compute Confidence Intervals/Bands and P-values After a TransformationtransformCIBP
Logistic Regression Using IPCWwglm