Basic ROC Analysis

To access this set of programs, in Stata type:
.net from 

You will be asked which package you wish to install. Click on pcvsuite. This will currently install four commands: roccurve, comproc, rocreg and inroc. A description of how to use them is obtained by using the help facility, e.g., help roccurve opens a window that explains the syntax and option for the roccurve command. A copy of the help files can be obtained here: roccurvecomprocrocreg and incroc.

Briefly, the roccurve command plots an estimate of the ROC curve for one or more diagnostic tests (or biomarkers). Confidence intervals can be displayed for the TPF (true positive fraction) corresponding to a specified FPF (false positive fraction). Confidence intervals are calculated using the bootstrap. The comproc command calculates summary ROC indices for two tests along with confidence intervals for each and for the difference. A p-value for testing equality of the ROCs based on the summary indices is output. The rocreg command fits an ROC-GLM regression model. Covariate adjustment is accommodated in all three commands.

To update the pcvsuite commands at a later time, in Stata type:
adoupdate, update

To uninstall the pcvsuite type:
ado uninstall pcvsuite

Additionally, two articles have been published in the Stata Journal describing these commands:
Pepe, M.S., Longton G, Janes, H. 2009. Estimation and comparison of receiver operating characteristic curves. Stata Journal 9(1),1-16.
Janes, H., Longton G, Pepe, M.S. 2009. Accommodating covariates in receiver operating characteristic analysis. Stata Journal 9(1),17-39.