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Re: st: Concordance


From   Tom Trikalinos <ttrikalin@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Concordance
Date   Fri, 12 Mar 2010 17:02:06 -0500

Hi ricardo,

i'm off to a meeting -- thus not time for a proper response, but these
are pointers.

1. difference vs average plots
2. Lin's concoradance correlation coefficient rather than Pearson correlation
3. (reduced) major axis regression and related regressions ([weighted
] Deming, Passing-Bablock[spelling may be off?]) rather than OLS>


ssc install concord

will get you quite far actually.
N. orsini had written a deming routine i f I racall correctly.

take care,

t



Thomas A Trikalinos MD, PhD

Co-Director Tufts Evidence-based Practice Center
Associate Director, Center for Clinical Evidence Synthesis

Institute for Clinical Research and Health Policy Studies
Tufts Medical Center | 800 Washington St | Boston, 02111 MA

Phone: +1 617 636 0734
Fax:   +1 617 636 8628
email: ttrikalinos@tuftsmedicalcenter.org







On Fri, Mar 12, 2010 at 1:57 PM, Ricardo Ovaldia <ovaldia@yahoo.com> wrote:
> Dear Statalist,
>
> Glucose on 100 serum samples was measured by two different methods. I would like to examine the concordance between the two set of measurements. The glucose values are continuous, so I was thinking about simply computing Pearson’s correlation coefficient, but that seems too simple and the test is not very sensitive. Is there a better way to assess concordance between two repeated measurements.
>
> Thank you,
>
> Ricardo
>
> Ricardo Ovaldia, MS
> Statistician
> Oklahoma City, OK
>
>
>
>
>
>
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