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# st: RE: McNemar's test with clustering

 From "Lachenbruch, Peter" To "'statalist@hsphsun2.harvard.edu'" Subject st: RE: McNemar's test with clustering Date Mon, 26 Apr 2010 09:58:40 -0700

```I seem to be missing something here.  If you take the within-pair difference aren't you removing the pair effect?
You can make the same argument for a dichotomous response. In this case the difference will be -1, 0, or 1.  You could do a t-test on this (variance would be slightly off) or you could look at the table of responses and test if the proportion of -1s is the same as the proportion of +1s.  May need to do this by hand, but should be simple.
What is the clustering variable if not pairs?

Tony

Peter A. Lachenbruch
Department of Public Health
Oregon State University
Corvallis, OR 97330
Phone: 541-737-3832
FAX: 541-737-4001

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Laura Gibbons
Sent: Sunday, April 25, 2010 6:39 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: McNemar's test with clustering

I'd like to do something like McNemar's test, -mcc-, where I'm comparing
presence of two dichotomous traits in each person.  [In this case, is a
finding more common on the left side of the spine, compared to the right.]

The problem is that the subjects are twins, in this analysis a nuisance
parameter, but svyset or cluster(pair) are not options for mcc.

For continuous outcomes I can get the equivalent of a paired t-test by
computing the difference and then getting the p-values from the intercept
in

reg difference, cluster(pair)

but I've not come up with anything along these lines either.

Any guidance would be appreciated, thanks!

-Laura

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Laura E. Gibbons, PhD
General Internal Medicine, University of Washington
Box 359780, Harborview Medical Center, 325 Ninth Ave, Seattle, WA 98104
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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