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

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) <doi:10.1111/j.0006-341X.2000.00337.x>. 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) <doi:10.1111/j.1541-0420.2011.01640.x>. 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) <doi:10.1111/j.0006-341X.2004.00200.x>.

Version: 0.9.5
Depends: R (≥ 2.10), splines, date, survival, relsurv, timereg
Published: 2017-02-19
Author: Y. Foucher, E. Dantan, F. Le Borgne, and M. Lorent
Maintainer: Y. Foucher <Yohann.Foucher at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: Survival
CRAN checks: ROCt results


Reference manual: ROCt.pdf
Package source: ROCt_0.9.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: ROCt_0.9.5.tgz, r-oldrel: ROCt_0.9.5.tgz
Old sources: ROCt archive


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