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RE: st: Sensitivity and specificity graphs for binary vars


From   "King, Carina" <c.king09@imperial.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Sensitivity and specificity graphs for binary vars
Date   Wed, 23 May 2012 12:51:52 +0000

Hi,

I realise any graphs are not really necessary here, I just much prefer visual presentations where they're possible (and obviously only if they are appropriate!). I was hoping for some help with the detection error trade-off graph mainly, as I couldn't really find anything about making them in Stata? Or whether it would be the best thing? Thanks!

Carina

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox
Sent: 23 May 2012 13:41
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Sensitivity and specificity graphs for binary vars

Why do you need or want a graph at all?(*) All the information is summarised efficiently by those four totals.

Nick

(*) Longstanding Statalist members are asked not to quote me saying this out of context.

On Wed, May 23, 2012 at 1:29 PM, King, Carina <c.king09@imperial.ac.uk> wrote:

> I have two binary variables, one being a 'gold standard' indicator of infection and the other based on a coded predictor. I have calculated the sensitivity and specificity (using -diagt-) of the coded predictor for identifying the 'gold standard' infections, but want to represent it graphically. I have looked at the ROC commands, including -roctab- and -roccomp- but don't think these are right as both my variables binary variables. My questions are whether a Detection Error Trade-Off graph is appropriate? Or is there another type of graph that would show the sensitivity and specificity well? And are they possible in Stata?
>
> I am using Stata SE 11
>
> Two-way table of my data:
>
>                Negative (gold standard) Positive (gold standard) 
> Negative (coded)        542 (true neg)          9 (false neg) Positive 
> (coded)        21 (false pos)          26 (true pos)
>

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