Hi Rasanga, you may have a look at the 'improveProb' function from the Hmisc package. There you can compare the increase in prognostic power for several combinations of markers. You can create a ROC curve for a combination of markers by using the predicted risks eg. from a logistic regression model.
To compare ROC curves of competing markers you can use 'roc.area.test' from the 'clinfun' package or 'hanley' from gcl. hth. Am 27.04.2011 23:17, schrieb Rasanga Ruwanthi: > Dear list > > I have 5 markers that can be used to detect an infection in combination. > Could you please advise me how to use functions in ROCR/ other package to > produce the ROC curve for a combination of markers? > > I have used the following to get ROC statistics for each marker. > pred <- prediction(y$marker1, y$infectn) > perf <-performance(pred,"tpr","fpr") > plot(perf,ave="threshold",spread.estimate="boxplot") > > But I want know whether we could get this for more than one marker, so we can > look at how good the markers in combination to predict the infection. I'm > very grateful for any suggestion/help. > > Thanks > Rasanga > > > [[alternative HTML version deleted]] > > > > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Eik Vettorazzi Institut für Medizinische Biometrie und Epidemiologie Universitätsklinikum Hamburg-Eppendorf Martinistr. 52 20246 Hamburg T ++49/40/7410-58243 F ++49/40/7410-57790 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
