MedCalc

 MedCalc provides the following capabilities for analyzing ROC curves. Most are found under the Statistics->ROC Curves menu.

• Enter data through manual input into an internal spreadsheet or import data through Excel, SPSS, or several other programs.
• Under "ROC analysis", plot a single ROC curve (with optional confidence bounds). The output is a graph, with the optimal cutpoint marked on the graph. Additional output includes AUC and its 95% confidence interval, and a table with the sensitivity and specificity at several cut-points, with their 95% confidence intervals.
• Under "Interactive dot-diagram", plot the observed values as points, and interactively move the cut-point around to find the sensitivity and specificity of the test.
• Under "Plot versus criterion", plot the sensitivity and specificity versus different cut-points, with optional 95% confidence intervals.
• Under "Comparison of ROC curves", plot up to 6 different ROC curves, get the AUCs for each plot, and the pairwise-comparisons between curves.
• Under "Predictive values", manually enter sensitivity, specificity, and prevalence to get out the positive predictive value and negative predictive value.
• It is possible to alter the format of graphs and export as an image.