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ROCt (version 0.8)

ROCt-package: Time-dependent ROC curves estimation

Description

Compute time-dependent ROC curve using Kaplan-Meier (KM) estimator or the k-nearest neighbor's (KNN) adaptation. Both approaches are developed for traditional survival analysis (all-cause analysis) and for the the additive relative survival analysis.

Arguments

Details

ll{ Package: ROCt Type: Package Version: 0.8 Date: 2013-12-20 License: GPL (>=2) LazyLoad: yes } Compute time-dependent ROC curve using Kaplan-Meier (KM) or the k-nearest neighbor's (KNN) adaptation. Both approaches are developed for traditional survival analysis (all-cause analysis) and for the additive relative survival analysis: rl{ allcause.ROCt This function performs the characteristics of a time-dependent ROC curve. net.ROCt This function performs the characteristics of a net time-dependent ROC curve . }

References

Heagerty PJ., Lumley T., Pepe MS. (2000) Time-dependent ROC Curves for Censored Survival Data and a Diagnostic Marker. Biometrics, 56, 337-344. Pohar M., Stare J. (2006) Relative survival analysis in R. Computer methods and programs in biomedicine, 81, 272-278. Pohar M., Stare J., Esteve J. (2012) On Estimation in Relative Survival. Biometrics, 68, 113-120. Akritas MG. (1994) Nearest neighbor estimation of a bivariate distribution under random censoring. Annals of Statistics, 22, 1299-1327. Lorent M., Giral M., Foucher Y. (2013) Net time-dependent ROC curves: a solution for evaluating the accuracy of a marker to predict disease-related mortality. Statistics in Medicine. In press.

See Also

URL: http://www.divat.fr