Install

library(devtools)
install_github("tagteam/riskRegression")

References

The following references provide the methodological framework for the features of riskRegression.

1. T.A. Gerds and M. Schumacher. Consistent estimation of the expected Brier score in general survival models with right-censored event times. Biometrical Journal, 48(6):1029–1040, 2006.
2. T.A. Gerds and M. Schumacher. Efron-type measures of prediction error for survival analysis. Biometrics, 63(4):1283–1287, 2007.
3. T.A. Gerds, T. Cai, and M. Schumacher. The performance of risk prediction models. Biometrical Journal, 50(4):457–479, 2008.
4. U B Mogensen, H. Ishwaran, and T A Gerds. Evaluating random forests for survival analysis using prediction error curves. Journal of Statistical Software, 50(11), 2012.
5. P. Blanche, J-F Dartigues, and H. Jacqmin-Gadda. Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks. Statistics in Medicine, 32(30): 5381–5397, 2013.
6. Paul Blanche, Ce’cile Proust-Lima, Lucie Loube`re, Claudine Berr, Jean- Franc,ois Dartigues, and He’le`ne Jacqmin-Gadda. Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks. Biometrics, 71 (1):102–113, 2015.

Functions predict.CauseSpecificCox, predictCox and iidCox:

• Brice Ozenne, Anne Lyngholm Sorensen, Thomas Scheike, Christian Torp-Pedersen and Thomas Alexander Gerds. riskRegression: Predicting the Risk of an Event using Cox Regression Models. The R Journal (2017) 9:2, pages 440-460.