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Re: st: ROC-curves

From   "Seed, Paul" <>
To   "" <>
Subject   Re: st: ROC-curves
Date   Fri, 18 Oct 2013 08:23:12 +0000

On 14/10/2013 18:54, Ragnhild Bergene Skråstad wrote:
 > Hi!
 > I investigate how different tests, in combination, can predict a given 
 > I have made a logistic model with the command "logistic" and plotted 
the ROC-curve with the command "lroc". This cave me the ROC-curve and 
the AUC. I wonder:
 > - how can I get the 95 % CI for this AUC?
 > and
 > - I would like to get the sensitivity at a given fixed false-positive 
rate. Do I have to get all the coordinates on the ROC curve and identify 
the one at the FPR at interest- and if so, how do I do that, or is it a 
direct way to do this?
 > best wishes
 > Ragnhild B Skråstad

The simplest way to get CI for a roc curve following logistic regression 
is to use -predict- and -roctab-:

* Start Stata commands *
logistic outcome <predictors>
capture drop pred
predict pred
roctab outcome pred

* End Stata commands *

* outcome and <predictors> are replaced as appropriate.
Much quicker and less trouble than bootstrapping.

To find the appropriate cutpoint for a given sensitivity you can use -centile- with -if-
centile pred if outcome == 1, centile(90)
Likewise for specificity
centile pred if outcome == 0, centile(10)

Best wishes, 

Paul T Seed, Women's Health, KCL

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