ARR | Risk Regression Fits a regression model for the risk of an event - allowing for competing risks. |
as.data.table.predictCox | Turn predictCox object into a 'data.table' |
as.data.table.predictCSC | Turn predictCSC object into a 'data.table' |
ate | Compute the average treatment effects via the g-formula |
autoplot.ate | Plot predictions from a Cause-specific Cox proportional hazard regression |
autoplot.predictCox | Plot predictions from a Cox model |
autoplot.predictCSC | Plot predictions from a Cause-specific Cox proportional hazard regression |
boot2pvalue | Compute the p.value from the distribution under H1 |
boxplot.Score | Boxplot risk quantiles |
calcSeCox | Computation of standard errors for predictions |
calcSeCSC | Standard error of the absolute risk predicted from cause-specific Cox models |
coef.CauseSpecificCox | Extract coefficients from a Cause-Specific Cox regression model |
coef.riskRegression | Extract coefficients from riskRegression model |
colCenter_cpp | Apply - by column |
colCumSum | Apply cumsum in each column |
colMultiply_cpp | Apply * by column |
colScale_cpp | Apply / by column |
colSumsCrossprod | Apply crossprod and colSums |
confBandCox | Compute quantiles of a gaussian process |
coxBaseEstimator | Extract the type of estimator for the baseline hazard |
coxBaseEstimator.coxph | Extract the type of estimator for the baseline hazard |
coxBaseEstimator.phreg | Extract the type of estimator for the baseline hazard |
coxCenter | Extract the mean value of the covariates |
coxCenter.coxph | Extract the mean value of the covariates |
coxCenter.cph | Extract the mean value of the covariates |
coxCenter.phreg | Extract the mean value of the covariates |
coxDesign | Extract the design matrix used to train a Cox model |
coxDesign.coxph | Extract the design matrix used to train a Cox model |
coxDesign.phreg | Extract the design matrix used to train a Cox model |
coxFormula | Extract the formula from a Cox model |
coxFormula.coxph | Extract the formula from a Cox model |
coxFormula.cph | Extract the formula from a Cox model |
coxFormula.phreg | Extract the formula from a Cox model |
coxLP | Compute the linear predictor of a Cox model |
coxLP.coxph | Compute the linear predictor of a Cox model |
coxLP.cph | Compute the linear predictor of a Cox model |
coxLP.phreg | Compute the linear predictor of a Cox model |
coxN | Extract the number of observations from a Cox model |
coxN.coxph | Extract the number of observations from a Cox model |
coxN.cph | Extract the number of observations from a Cox model |
coxN.phreg | Extract the number of observations from a Cox model |
coxSpecialStrata | Special character for strata in Cox model |
coxSpecialStrata.coxph | Special character for strata in Cox model |
coxSpecialStrata.cph | Special character for strata in Cox model |
coxSpecialStrata.phreg | Special character for strata in Cox model |
coxStrata | Define the strata for a new dataset |
coxStrata.coxph | Define the strata for a new dataset |
coxStrata.cph | Define the strata for a new dataset |
coxStrata.phreg | Define the strata for a new dataset |
coxVarCov | Extract the variance covariance matrix of the beta from a Cox model |
coxVarCov.coxph | Extract the variance covariance matrix of the beta from a Cox model |
coxVarCov.cph | Extract the variance covariance matrix of the beta from a Cox model |
coxVarCov.phreg | Extract the variance covariance matrix of the beta from a Cox model |
coxVariableName | Extract variable names from a model |
CSC | Cause-specific Cox proportional hazard regression |
discreteRoot | Dichotomic search for monotone function |
extractStrata | Extract the information about the strata |
FGR | Formula wrapper for crr from cmprsk |
getSplitMethod | Input for data splitting algorithms |
iidCox | Extract i.i.d. decomposition from a Cox model |
influenceCoxTest | Influence test [Experimental!!] |
influenceCoxTest.default | Influence test [Experimental!!] |
influenceCoxTest.list | Influence test [Experimental!!] |
IPA | Explained variation for settings with binary, survival and competing risk outcome |
IPA.CauseSpecificCox | Explained variation for settings with binary, survival and competing risk outcome |
IPA.coxph | Explained variation for settings with binary, survival and competing risk outcome |
IPA.default | Explained variation for settings with binary, survival and competing risk outcome |
IPA.glm | Explained variation for settings with binary, survival and competing risk outcome |
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 |
LRR | Risk Regression Fits a regression model for the risk of an event - allowing for competing risks. |
Melanoma | Malignant melanoma data |
model.matrix.phreg | Extract design matrix for phreg objects |
Paquid | Paquid sample |
penalizedS3 | S3-wrapper for S4 function penalized |
plot.riskRegression | Plotting predicted risk |
plotAUC | ggplot AUC curve |
plotBrier | Plot Brier curve |
plotCalibration | Plot Calibration curve |
plotEffects | Plotting time-varying effects from a risk regression model. |
plotRisk | plot predicted risks |
plotROC | Plot ROC curves |
predict.CauseSpecificCox | Predicting absolute risk from cause-specific Cox models |
predict.FGR | Predict subject specific risks (cumulative incidence) based on Fine-Gray regression model |
predict.riskRegression | Predict individual risk. |
predictCox | Fast computation of survival probabilities, hazards and cumulative hazards from Cox regression models |
predictCoxPL | Computation of survival probabilities from Cox regression models using the product limit estimator. |
predictRisk | Extrating predicting risks from regression models |
predictRisk.aalen | Extrating predicting risks from regression models |
predictRisk.CauseSpecificCox | Extrating predicting risks from regression models |
predictRisk.cox.aalen | Extrating predicting risks from regression models |
predictRisk.coxph | Extrating predicting risks from regression models |
predictRisk.cph | Extrating predicting risks from regression models |
predictRisk.default | Extrating predicting risks from regression models |
predictRisk.FGR | Extrating predicting risks from regression models |
predictRisk.glm | Extrating predicting risks from regression models |
predictRisk.lrm | Extrating predicting risks from regression models |
predictRisk.matrix | Extrating predicting risks from regression models |
predictRisk.pecCforest | Extrating predicting risks from regression models |
predictRisk.pecCtree | Extrating predicting risks from regression models |
predictRisk.prodlim | Extrating predicting risks from regression models |
predictRisk.psm | Extrating predicting risks from regression models |
predictRisk.randomForest | Extrating predicting risks from regression models |
predictRisk.rfsrc | Extrating predicting risks from regression models |
predictRisk.riskRegression | Extrating predicting risks from regression models |
predictRisk.rpart | Extrating predicting risks from regression models |
predictRisk.selectCox | Extrating predicting risks from regression models |
predictRisk.survfit | Extrating predicting risks from regression models |
print.ate | Print average treatment effects |
print.CauseSpecificCox | Print of a Cause-Specific Cox regression model |
print.FGR | Print of a Fine-Gray regression model |
print.influenceCoxTest | Print the results of the influence test |
print.predictCox | Print predictions from a Cox model |
print.predictCSC | Print predictions from a Cause-specific Cox proportional hazard regression |
print.riskRegression | Print function for riskRegression models |
print.Score | Print Score object |
print.subjectWeights | Print subject weights |
reconstructData | Reconstruct the original dataset |
riskRegression | Risk Regression Fits a regression model for the risk of an event - allowing for competing risks. |
rowCenter_cpp | Apply - by row |
rowCumSum | Apply cumsum in each row |
rowMultiply_cpp | Apply * by row |
rowScale_cpp | Apply / by row |
rowSumsCrossprod | Apply crossprod and rowSums |
rsquared | Explained variation for settings with binary, survival and competing risk outcome |
rsquared.CauseSpecificCox | Explained variation for settings with binary, survival and competing risk outcome |
rsquared.coxph | Explained variation for settings with binary, survival and competing risk outcome |
rsquared.default | Explained variation for settings with binary, survival and competing risk outcome |
rsquared.glm | Explained variation for settings with binary, survival and competing risk outcome |
sampleData | Simulate data with binary or time-to-event outcome |
sampleDataTD | Simulate data with binary or time-to-event outcome |
Score | Score risk predictions |
Score.list | Score risk predictions |
selectCox | Backward variable selection in the Cox regression model |
selectJump | Evaluate the influence function at selected times |
simMelanoma | Simulate data alike the Melanoma data |
sliceMultiply_cpp | Apply * by slice |
sliceScale_cpp | Apply / by slice |
splitStrataVar | Reconstruct each of the strata variables |
subjectWeights | Estimation of censoring probabilities at subject specific times |
subjectWeights.aalen | Estimation of censoring probabilities at subject specific times |
subjectWeights.cox | Estimation of censoring probabilities at subject specific times |
subjectWeights.km | Estimation of censoring probabilities at subject specific times |
subjectWeights.marginal | Estimation of censoring probabilities at subject specific times |
subjectWeights.none | Estimation of censoring probabilities at subject specific times |
subjectWeights.nonpar | Estimation of censoring probabilities at subject specific times |
summary.FGR | Summary of a Fine-Gray regression model |
summary.riskRegression | Summary of a risk regression model |
SurvResponseVar | Extract the time and event variable from a Cox model |