Two or three years ago, I started into an SROC Stata program following the method of Littenberg and Moses. My code was based, in
part, on some Stata code written by Ben Littenberg but never published. The code performs a meta-analysis of AUC's as well as some
diagnostic tests.
Ben and I started an exchange on the functionality of the code but other tasks interfered and I had completed the specific work I
needed to do, so I never returned to the SROC program. I seem to recall that Ben no longer believed that computations on Q* should
be done and he preferred to use the AUC from 0 to the max observed value rather than from 0 to 1 (as my code does).
Regardless, you a welcome to a copy of the code "as is". Drop me a note at [email protected] and I'll attach the ado, hlp and dlg to
a reply message.
Further, if anyone wants to develop this code further, I'd be happy to turn it over to you!
Tom
Thomas J. Steichen
[email protected]
----------------------------------------------------------------------------
Facts do not cease to exist because they are ignored. - Aldous Huxley
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> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of
> Tom Trikalinos
> Sent: Tuesday, December 13, 2005 1:28 PM
> To: [email protected]
> Subject: Re: st: meta-analysis and ROC
>
>
> Hi Andrei,
>
> Summary ROC (SROC) is not exactly a meta-analysis of "ROC"
> curves. It's
> somehow different.
> SROC provides a summary measure of diagnostic performance
> when you only
> have sensitivity & specificity values per study. Each study is
> represented by a pair of sensitivity-specificity values
> rather than the
> ROC curve. SROC was devised because often the cutoff points of the
> diagnostic test variables differ across studies, and in fact SROC is
> informative only when the cutoff points differ.
>
> If you really want to meta-analyze ROC curves, you can in principle
> meta-analyze AUC values with an inverse-variance model (you need the
> AUC variance for this).
>
> Otherwise you might be better off with a meta-analysis of sensitivity
> and specificity across studies, after selecting the same cutoffs for
> the patients of each center.
>
> Having all values for all patients, I might opt for different
> analyses
> rather than a SROC curve.
>
> For the record there's no module in Stata that does SROC analyses, to
> my knowledge at least. You could find the SROC manually in
> Stata, but
> it seems you don't want this.
>
> tom
>
>
>
>
> On Dec 12, 2005, at 10:07 PM, Andrei Malinovschi wrote:
>
> > Dear Statalisters,
> >
> > I am having a database where we are looking at
> > different symptoms (categorical variables) and
> > different diagnostic tests (continuous variables). The
> > data comes from several centers and we are trying a meta-analysis
> > approach because we can't pool the data (due to differences between
> > methods used in different centers).
> >
> > I would like to perform a meta-analysis on the ROC
> > curves and get the AUC for a specific test for all the
> centers for one
> > symptom (and then compare the AUCs for different tests for that
> > symptom). It appears that I would need to do a SROC, is it
> right?. I
> > couldn't find a program to perform SROC in STATA and I am wondering
> > if there is an easy way to do that (the hard way would
> > be to use -somersd- package, but it looks complicated
> > to me and I was lost somewhere among vectors and
> > diagonal matrices)?
> >
> > I welcome any comments regarding other approaches
> > (better ones or easier to perform) to answer my
> > question!
> >
> > Thank you in advance!
> >
> > With best regards,
> > Andrei
> >
> > __________________________________________________
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> >
> >
> Tom Trikalinos, MD
> [email protected]
>
> *
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