Thanks. library(ROCR) was used finally. It also automatically generate a plot beside the value of AUC. On Dec 31, 2007 11:38 PM, Frank E Harrell Jr wrote: > zhijie zhang wrote: > > Dear all, > > Some functions like 'ROC(Epi)' can be used to perform ROC analyssi, > but it > > needs us to specify the fitting model in the argument. Now i have got > the > > predicted p-values (0,1) for the 0/1 response variable using some other > > approach, see the following example dataset: > > > > id mark predict.pvalue > > > > 1 1 0.927 > > > > 2 0 0.928 > > > > 3 1 0.928 > > > > .................. > > > > *mark* is the true classes, *predict.pvalue* is the predicted p-values, > > which was used to determine the predicted classes. So i need to specify > some > > cut points for *predict.pvalue*, and then compare it with *mark*class, > > generate the 2*2 tables, and then calculate some sensitivity, > > specifity....statistcs, and ROC curve. > > I have searched some functions, such as roc(analogue),'ROC(Epi),etc. > They > > may need to specify the fitting model in the codes or group varibles, > > and may be not appropriate for my condition. I think that it should > > have been performed in some package for ROC analysis. > > Anybody can tell me which function is for this case? > > Thanks very much. > > Forming the ROC curve can lead to bad statistical practice, e.g., use of > non-pre-specified cutpoints and use of cutpoints in general. The area > under the ROC curve is a valid measure of predictive discrimination > though (even though it cannot be used to compare 2 models as it is not > sensitive enough). To get the ROC area you can use the simple somers2 > function in the Hmisc package. > > Frank > > -- > Frank E Harrell Jr Professor and Chair School of Medicine > Department of Biostatistics Vanderbilt University > -- With Kind Regards, oooO::::::::: (..)::::::::: :\.(:::Oooo:: ::\_)::(..):: :::::::)./::: ::::::(_/:::: ::::::::::::: [***********************************************************************] Zhi Jie,Zhang ,PHD Tel:+86-21-54237149 Dept. of Epidemiology,School of Public Health,Fudan University Address:No. 138 Yi Xue Yuan Road,Shanghai,China Postcode:200032 Email:epistat@gmail.com Website: www.statABC.com [***********************************************************************] oooO::::::::: (..)::::::::: :\.(:::Oooo:: ::\_)::(..):: :::::::)./::: ::::::(_/:::: ::::::::::::: [[alternative HTML version deleted]]