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RE: st: Concordance


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Concordance
Date   Sun, 14 Mar 2010 17:59:22 -0000

Thanks to Tom for mentioning -concord-, which is by Thomas Steichen and
myself. 

In fact, a more recent version of -concord- than that on SSC is
downloadable from the Stata Journal website, as -search concord-
indicates. 

If Ricardo had used -search concordance- he would got to this advice
from Tom Trikalinos and myself in a matter of seconds. 

The Statalist FAQ mentions the use of -search- as a way to solve your
problems, as do many introductions to Stata. 

Nick 
n.j.cox@durham.ac.uk 

Tom Trikalinos

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.

On Fri, Mar 12, 2010 at 1:57 PM, Ricardo Ovaldia <ovaldia@yahoo.com>
wrote:

> 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.

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