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riskRegression (version 1.4.3)

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

Description

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.

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Version

Install

install.packages('riskRegression')

Monthly Downloads

9,120

Version

1.4.3

License

GPL (>= 2)

Maintainer

Thomas Alexander Gerds

Last Published

June 30th, 2017

Functions in riskRegression (1.4.3)

CoxStrata

Define the strata for a new dataset
CoxVarCov

Extract the variance covariance matrix of the beta from a Cox model
CoxN

Extract the number of observations from a Cox model
CoxSpecialStrata

Special character for strata in Cox model
CSC

Cause-specific Cox proportional hazard regression
CoxBaseEstimator

Extract the type of estimator for the baseline hazard
CoxFormula

Extract the formula from a Cox model
CoxLP

Compute the linear predictor of a Cox model
CoxCenter

Extract the mean value of the covariates
CoxDesign

Extract the design matrix used to train a Cox model
CoxVariableName

Extract variable names from a model
FGR

Formula wrapper for crr from cmprsk
as.data.table.predictCSC

Turn predictCSC object into a data.table
as.data.table.predictCox

Turn predictCox object into a data.table
boxplot.Score

Boxplot risk quantiles
IFlambda2hazard

Evaluate the influence function for the hazard based on the one of the baseline hazard##'
Melanoma

Malignant melanoma data
colCumSum

Apply cumsum in each column
colMultiply_cpp

Apply * by column
model.matrix.phreg

Extract design matrix for phreg objects
penalizedS3

S3-wrapper for S4 function penalized
plotRisk

plot predicted risks
predict.CauseSpecificCox

Predicting absolute risk from cause-specific Cox models
print.Score

Print Score object
print.ate

Print average treatment effects
ate

Compute the average treatment effect using CSC.
autoplot.ate

Plot predictions from a Cause-specific Cox proportional hazard regression
autoplot.predictCSC

Plot predictions from a Cause-specific Cox proportional hazard regression
autoplot.predictCox

Plot predictions from a Cox model
calcSeCSC

Standard error of the absolute risk predicted from cause-specific Cox models
iid

Extract i.i.d. decomposition from a Cox model
plot.riskRegression

Plotting predicted risk
colScale_cpp

Apply / by column
colSumsCrossprod

Apply crossprod and colSums
plotEffects

Plotting time-varying effects from a risk regression model.
Score.list

Score risk predictions
SurvResponseVar

Extract the time and event variable from a Cox model
coef.riskRegression

Extract coefficients from riskRegression model
colCenter_cpp

Apply - by column
findP1

Compute the p.value from the distribution under H1
influenceTest

Influence test [Experimental!!]
ipcw

Estimation of censoring probabilities
plotBrier

Plot Brier curve
plotCalibration

Plot Calibration curve
print.riskRegression

Print function for riskRegression models
print.subjectWeights

Print subject weights
riskRegression

Risk Regression Fits a regression model for the risk of an event -- allowing for competing risks.
rowCenter_cpp

Apply - by row
plotROC

Plot ROC curves
predictCox

Fast computation of survival probabilities, hazards and cumulative hazards from Cox regression models
predictRisk

Extrating predicting risks from regression models
sampleData

Simulate data with binary or time-to-event outcome
selectJump

Evaluate the influence function at selected times
sliceScale_cpp

Apply / by slice
calcSeCox

Computation of standard errors for predictions
coef.CauseSpecificCox

Extract coefficients from a Cause-Specific Cox regression model
confBandCox

Compute quantiles of a gaussian process
extractStrata

Extract the information about the strata
plotAUC

Plot AUC curve
print.predictCSC

Print predictions from a Cause-specific Cox proportional hazard regression
print.predictCox

Print predictions from a Cox model
rowCumSum

Apply cumsum in each row
predict.FGR

Predict subject specific risks (cumulative incidence) based on Fine-Gray regression model
predict.riskRegression

Predict individual risk.
print.CauseSpecificCox

Print of a Cause-Specific Cox regression model
print.FGR

Print of a Fine-Gray regression model
rowMultiply_cpp

Apply * by row
rowScale_cpp

Apply / by row
rowSumsCrossprod

Apply crossprod and rowSums
summary.FGR

Summary of a Fine-Gray regression model
summary.riskRegression

Summary of a risk regression model
simMelanoma

Simulate data alike the Melanoma data
sliceMultiply_cpp

Apply * by slice
subjectWeights

Estimation of censoring probabilities at subject specific times