pROC 1.3 released

I just released the version 1.3 of pROC.

This function introduces several bug fixes and speed improvements, along with some new features. You can detect if two ROC curves are paired:

library(pROC)
data(aSAH)
rocs100 <- roc(aSAH$outcome, aSAH$s100)
rocwfns <- roc(aSAH$outcome, aSAH$wfns)
are.paired(rocs100, rocwfns)

A new method for the roc.test is also introduced: the Venkatraman's test1. Unlike bootstrap and DeLong2 methods, it doesn't assess the equality of the AUC. Instead, it looks at the shape of ROC curves. Two ROC curves with the same AUC but a different shape will be significantly different

set.seed(1)
response <- round(runif(1000, 0, 1))
predictor1 <- response + rnorm(1000)
predictor2 <- response + rlnorm(1000)

roc1 <- roc(response, predictor1, plot=TRUE)
roc2 <- roc(response, predictor2, plot=TRUE, add=TRUE)

roc.test(roc1, roc2)
roc.test(roc1, roc2, method="venkatraman", boot.n=200)

I generate two artificial ROC curves. Their AUC is not different, and the DeLong test gives a non significant result. However their shapes are highly dissimilar, and the Venkatraman's test finds a significant difference.

Here is the full change log:

As usual, you can find the new version on ExPASy and on the CRAN. To update, type update.packages() or install.packages("pROC") if you want to update pROC only.

Xavier Robin
Published Friday, August 13, 2010 18:35 CEST
Permalink: /blog/2010/08/13/proc-1.3-released
Tags: pROC
Comments: 0

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