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Re: st: RE: McNemar's test with clustering


From   Laura Gibbons <gibbonsl@u.washington.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: RE: McNemar's test with clustering
Date   Mon, 26 Apr 2010 11:12:48 -0700 (PDT)

Thank you everyone for your help with this. Here is one solution, based on your hints, demonstrated on some randomly generated sample data. For this approach, I need to have 2 records/person, one for each side.

clear
set obs 200
set seed 42610
gen id=floor((_n+1)/2)
gen outcome=round(uniform())
bys id:gen side=_n
gen pair=floor((id+1)/2)

/*   id  outcome  side  pair
  1.  1        0     1     1
  2.  1        1     2     1
  3.  2        1     1     1
  4.  2        0     2     1
  5.  3        1     1     2
  6.  3        0     2     2
  7.  4        1     1     2
  8.  4        0     2     2
	etc */

clogit out side, group(id) vce(cluster pair)

I will also pursue -somersd- because Roger is correct that my audience would prefer a difference in proportions.

Thanks again for your quick and helpful replies.  -Laura

On Mon, 26 Apr 2010, Roger Newson wrote:

Yes, you could treat twin pairs as a block. However, as we are sampling twin pairs from a population of twin pairs, I would still cluster by twin pair, whether I was using -clogit- or -somersd-.

The -somersd- method has the advantage that it outputs a difference between proportions. I think more people understand those than understand odds ratios, although odds ratios are useful for estimating relative risks in a case-control study.

Best wishes

Roger


Roger B Newson BSc MSc DPhil
Lecturer in Medical Statistics
Respiratory Epidemiology and Public Health Group
National Heart and Lung Institute
Imperial College London
Royal Brompton Campus
Room 33, Emmanuel Kaye Building
1B Manresa Road
London SW3 6LR
UNITED KINGDOM
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Email: r.newson@imperial.ac.uk
Web page: http://www.imperial.ac.uk/nhli/r.newson/
Departmental Web page:
http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/popgenetics/reph/

Opinions expressed are those of the author, not of the institution.

On 26/04/2010 18:36, Lachenbruch, Peter wrote:
Could you treat the members of the twin pairs as a block in a randomized block fashion? The clogit idea sounds pretty good

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: Monday, April 26, 2010 10:10 AM
To: 'statalist@hsphsun2.harvard.edu'
Subject: Re: st: RE: McNemar's test with clustering

Sorry this wasn't clear.  For this analysis, I'm just interested in the
men as individuals, are their right and left sides different.  If I had a
continous outcome (and no twinship to consider), I'd use a paired t-test.

But the sample happens to be (for other reasons) twins, so I need to
adjust errors (p-values) for the correlation between twins.

Pair	Twin	Left 	Right
-----------------------------
1	1	1	0
1	2	1	1
2	1	0	0
2	2	1	0

something like that, where I wan't to compare Left and Right, and Pair is
a nuisance variable to me.

thank you!  Laura


On Mon, 26 Apr 2010, Lachenbruch, Peter wrote:

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
phone: 206-744-1842, fax: 206-744-9917, Office address: 401 Broadway, Suite 5122
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Laura E. Gibbons, PhD
General Internal Medicine, University of Washington
Box 359780, Harborview Medical Center, 325 Ninth Ave, Seattle, WA 98104
phone: 206-744-1842, fax: 206-744-9917, Office address: 401 Broadway, Suite 5122
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
*
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*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/

*
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Laura E. Gibbons, PhD
General Internal Medicine, University of Washington
Box 359780, Harborview Medical Center, 325 Ninth Ave, Seattle, WA 98104
phone: 206-744-1842, fax: 206-744-9917, Office address: 401 Broadway, Suite 5122
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


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