NPROC: Stata module to produce nonparametric receiver operating curves

Philip Price () and Fred Wolfe ()

Statistical Software Components from Boston College Department of Economics

Abstract: nproc calculates nonparametric AUCs and standard errors for ROC curves for the varlist. If more than 2 curves are requested, a chi-square test for the difference between the first and subsequent curves is calculated. The default graph option displays the graph of each variable as the statistics are being calculated. In addition, the default graph option saves sensitivity and specificity data, AUCs, standard errors, and Chi-square and p-value data to an output file for subsequent analysis by the companion graph program, rocgraph. While graphs are being displayed by nproc and statistics calculated, graphs may be selected and printed. rocgraph also displays summary statistics. ROC analysis is a method of measuring and comparing the accuracy of one or more variables at predicting whether each observation is a member of one of two groups/categories. The ROC curve plots the Sensitivity (True Positive rate) against 1-Specificity (False Positive rate). The larger the Area Under the ROC Curve (AUC) , the better the variable is at predicting group membership.

Language: Stata
Date: 1998-09-17

Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/n/nproc.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/r/rocplot.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/r/rocauc.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/r/rocse.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/r/roccov.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/n/nproc.hlp help file (text/plain)

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