| calPlot | Calibration plots for right censored data |
| cindex | Concordance index for right censored survival time data |
| cost | Copenhagen Stroke Study |
| coxboost | Formula interface for function 'CoxBoost' of package 'CoxBoost'. |
| crps | Summarizing prediction error curves |
| GBSG2 | German Breast Cancer Study Group 2 |
| ibs | Summarizing prediction error curves |
| ipcw | Estimation of censoring probabilities |
| ipcw.aalen | Estimation of censoring probabilities |
| ipcw.cox | Estimation of censoring probabilities |
| ipcw.marginal | Estimation of censoring probabilities |
| ipcw.none | Estimation of censoring probabilities |
| ipcw.nonpar | Estimation of censoring probabilities |
| Pbc3 | Pbc3 data |
| pec | Prediction error curves |
| pecCforest | S3-wrapper function for cforest from the party package |
| plot.pec | Plotting prediction error curves |
| plotPredictEventProb | Plotting predicted survival curves. |
| plotPredictSurvProb | Plotting predicted survival curves. |
| predictEventProb | Predicting event probabilities (cumulative incidences) in competing risk models. |
| predictEventProb.CauseSpecificCox | Predicting event probabilities (cumulative incidences) in competing risk models. |
| predictEventProb.FGR | Predicting event probabilities (cumulative incidences) in competing risk models. |
| predictEventProb.prodlim | Predicting event probabilities (cumulative incidences) in competing risk models. |
| predictEventProb.rfsrc | Predicting event probabilities (cumulative incidences) in competing risk models. |
| predictEventProb.riskRegression | Predicting event probabilities (cumulative incidences) in competing risk models. |
| predictLifeYearsLost | Predicting life years lost (cumulative cumulative incidences) in competing risk models. |
| predictLifeYearsLost.CauseSpecificCox | Predicting life years lost (cumulative cumulative incidences) in competing risk models. |
| predictLifeYearsLost.FGR | Predicting life years lost (cumulative cumulative incidences) in competing risk models. |
| predictLifeYearsLost.prodlim | Predicting life years lost (cumulative cumulative incidences) in competing risk models. |
| predictLifeYearsLost.rfsrc | Predicting life years lost (cumulative cumulative incidences) in competing risk models. |
| predictLifeYearsLost.riskRegression | Predicting life years lost (cumulative cumulative incidences) in competing risk models. |
| predictSurvProb | Predicting survival probabilities |
| predictSurvProb.aalen | Predicting survival probabilities |
| predictSurvProb.cox.aalen | Predicting survival probabilities |
| predictSurvProb.coxph | Predicting survival probabilities |
| predictSurvProb.cph | Predicting survival probabilities |
| predictSurvProb.default | Predicting survival probabilities |
| predictSurvProb.matrix | Predicting survival probabilities |
| predictSurvProb.mfp | Predicting survival probabilities |
| predictSurvProb.pecCforest | Predicting survival probabilities |
| predictSurvProb.phnnet | Predicting survival probabilities |
| predictSurvProb.prodlim | Predicting survival probabilities |
| predictSurvProb.psm | Predicting survival probabilities |
| predictSurvProb.rfsrc | Predicting survival probabilities |
| predictSurvProb.riskRegression | Predicting survival probabilities |
| predictSurvProb.rpart | Predicting survival probabilities |
| predictSurvProb.selectCox | Predicting survival probabilities |
| predictSurvProb.survfit | Predicting survival probabilities |
| predictSurvProb.survnnet | Predicting survival probabilities |
| print.pec | Printing a 'pec' (prediction error curve) object. |
| R2 | Explained variation for survival models |
| resolvesplitMethod | Resolve the splitMethod for estimation of prediction performance |
| selectCox | Backward variable selection in the Cox regression model |
| selectFGR | Stepwise variable selection in the Fine & Gray regression competing risk model |
| simCost | Simulate COST alike data |
| Special | Drawing bootstrapped cross-validation curves and the .632 or .632plus error of models. The prediction error for an optional benchmark model can be added together with bootstrapped cross-validation error and apparent errors. |
| summary.pec | Printing a 'pec' (prediction error curve) object. |