[R-pkgs] pROC 1.4.3: compare two ROC curves in R

From: Xavier Robin <Xavier.Robin_at_unige.ch>
Date: Thu, 31 Mar 2011 17:23:08 +0200


Dear R users,

pROC is a package to compare, visualize, and smooth receiver operating characteristic (ROC) curves.

The package provides the following features:
* Partial or full area under the curve (AUC) computation

The main feature of pROC is the comparison between two ROC curves. Three methods are currently implemented for both paired and unpaired ROC curves:
* Bootstrap for full and partial AUC and smoothed ROC curves

Confidence intervals can be computed with bootstrap for both empirical or smoothed ROC curves:
* partial or full AUC (also with DeLong [1] method for full AUC)

You can find more information in our paper [4] and on pROC website: http://www.expasy.org/tools/pROC/

Hope you'll find it useful!

Xavier Robin

-- 
References:
[1] DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas
under two or more correlated receiver operating characteristic curves: a
nonparametric approach. Biometrics 44, 837–845.
[2] Venkatraman ES,Begg CB (1996) A distribution-free procedure for
comparing receiver operating characteristic curves from a paired
experiment. Biometrika 83, 835–848.
[3] Venkatraman ES (2000) A Permutation Test to Compare Receiver
Operating Characteristic Curves. Biometrics 56, 1134–1138.
[4] Robin X, Turck N, Hainard A, et al. (2011). pROC: an open-source
package for R and S+ to analyze and compare ROC curves. BMC
Bioinformatics, 12, 77. http://dx.doi.org/10.1186/1471-2105-12-77

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Received on Fri 01 Apr 2011 - 19:48:25 EST

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