ROCt: Time-Dependent ROC Curve Estimators and Expected Utility Functions
Version 0.9.5

Contains functions in order to estimate diagnostic and prognostic capacities of continuous markers. More precisely, one function concerns the estimation of time-dependent ROC (ROCt) curve, as proposed by Heagerty et al. (2000) . One function concerns the adaptation of the ROCt theory for studying the capacity of a marker to predict the excess of mortality of a specific population compared to the general population. This last part is based on additive relative survival models and the work of Pohar-Perme et al. (2012) . We also propose two functions for cut-off estimation in medical decision making by maximizing time-dependent expected utility function. Finally, we propose confounder-adjusted estimators of ROC and ROCt curves by using the Inverse Probability Weighting (IPW) approach. For the confounder-adjusted ROC curve (without censoring), we also proposed the implementation of the estimator based on placement values proposed by Pepe and Cai (2004) .

Package details

AuthorY. Foucher, E. Dantan, F. Le Borgne, and M. Lorent
Date of publication2017-02-19 15:46:38
MaintainerY. Foucher <[email protected]>
LicenseGPL (>= 2)
Version0.9.5
URL www.r-project.org www.divat.fr
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("ROCt")

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ROCt documentation built on May 30, 2017, 6:36 a.m.