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Re: st: Question on ROC analysis
From
Nick Cox <[email protected]>
To
[email protected]
Subject
Re: st: Question on ROC analysis
Date
Tue, 24 May 2011 16:01:58 +0100
Note also that Stata has a function -atanh()-.
Nick
On Tue, May 24, 2011 at 2:43 PM, Steven Samuels <[email protected]> wrote:
> Megan,
>
> Another advantage of using -somersd-: It can produce asymmetric confidence intervals for the AUC, which will often be more accurate for high or low values of the AUC. You do this by computing the intervals for Fisher's Z transform of Somers' D statistic, then transforming them by hand to intervals for the AUC ("Harrell's c").
>
> Ref: Roger Newson Confidence intervals for rank statistics: Somers’ D and extensions. The Stata Journal (2006) 6, Number 3, pp. 309–334 available at: http://www.stata-journal.com/article.html?article=snp15_6
>
> **************************CODE BEGINS*******
> sysuse auto, clear
> gen y = 1/mpg
> gen ylow = y<.05
> gen yhigh = 1-ylow
> gen x = weight
> gen nx = -x
>
> somersd ylow nx, tdist tr(z)
> matrix b = e(b)
> local z= b[1,1]
> matrix v=e(V)
> local v =v[1,1]
>
> local bound = sqrt(`v')*invttail(e(df_r),0.5*(1-c(level)/100))
> local ll = `z'-`bound'
> local ul = `z' + `bound'
> local auc = (exp(2*`z')-1)/(exp(2*`z')+1)
> local auc = (`auc'+1)/2
> local llim = (exp(2*`ll')-1)/(exp(2*`ll')+1)
> local llim = (`llim'+1)/2
> local ulim = (exp(2*`ul')-1)/(exp(2*`ul')+1)
> local ulim = (`ulim'+1)/2
> //asymmetric interval
> di "Asymmetric: auc ="%9.7g `auc' " llim ="%9.7g `llim' " ulim ="%9.7g `ulim'
> // compare to symmetric interval:
> somersd ylow nx, tdist tr(c)
> **************************CODE ENDS*******
>
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