I know how to compute the ROC curve and the empirical AUC from the logistic regression after fitting the model. But here is my question, how can I compute the standard error for the AUC estimator resulting form logistic regression? The variance should be more complicated than AUC based on known test results. Does anybody know a reference on this problem? [[alternative HTML version deleted]]
gallon li wrote:> I know how to compute the ROC curve and the empirical AUC from the logistic > regression after fitting the model. > > But here is my question, how can I compute the standard error for the AUC > estimator resulting form logistic regression? The variance should be more > complicated than AUC based on known test results. Does anybody know a > reference on this problem? >The rcorr.cens function in the Hmisc package will compute the std. error of Somers' Dxy rank correlation. Dxy = 2*(C-.5) where C is the ROC area. This standard error does not include a variance component for the uncertainty in the model (e.g., it does not penalize for the estimation of the regression coefficients if you are estimating the coefficients and assessing ROC area on the same sample). The lrm function in the Design package fits binary and ordinal logistic regression models and reports C, Dxy, and other measures. I haven't seen an example where drawing the ROC curve provides useful information that leads to correct actions. Frank -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University
Hi there, See ?lroc in the epicalc package. HTH, Jorge On Mon, Sep 8, 2008 at 4:02 AM, gallon li <gallon.li@gmail.com> wrote:> I know how to compute the ROC curve and the empirical AUC from the logistic > regression after fitting the model. > > But here is my question, how can I compute the standard error for the AUC > estimator resulting form logistic regression? The variance should be more > complicated than AUC based on known test results. Does anybody know a > reference on this problem? > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]