This package computes traditional ROC curves and time-dependent ROC curves using the cross-validation, the 0.632 and the 0.632+ estimators. The 0.632+ estimator of time-dependent ROC curve is useful to estimate the predictive accuracy of prognostic signature based on high-dimensional data. For instance, it outperforms the other approaches, especially the cross-validation solution which is often used. The 0.632+ estimators correct the area under the curve in order to adequately estimate the prognostic capacities regardless of the overfitting level. This package also allows for the construction of diagnostic or prognostic scoring systems (penalized regressions). The methodology is adapted to complete data (penalized logistic regression associated with ROC curve) or incomplete time-to-event data (penalized Cox model associated with time-dependent ROC curve).
|Author||Y. Foucher <Yohann.Foucher@univ-nantes.fr>|
|Date of publication||2013-12-27 22:22:51|
|Maintainer||Y. Foucher <Yohann.Foucher@univ-nantes.fr>|
|License||GPL (>= 2)|
AUC: Area under ROC curve from sensitivities and specificities
boot.ROC: Construction of a diagnostic or prognostic scoring system and...
boot.ROCt: Construction of a prognostic scoring system and estimation of...
DLBCLgenes: The data concerning the gene expressions of the DLBCL...
DLBCLpatients: The data concerning the clinical information of the DLBCL...
ROC: Estimation of the traditional ROC curves (without censoring)
ROC632-package: Estimation of prognostic capacity of microarray data.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.