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Re: st: metan and other meta-analysis commands in Stata


From   Jonathan Sterne <[email protected]>
To   Austin Nichols <[email protected]>, [email protected]
Subject   Re: st: metan and other meta-analysis commands in Stata
Date   Thu, 21 Dec 2006 13:22:15 -0000

We did discuss your comments about dealing with clustering, but I'm afraid we don't think that it would be appropriate to add anything to the metan help file as metan does not include facilities to deal with clustering. It is of course possible to use methods that allow for clustering to derive the treatment effect and its standard error in any trial where clustering is an issue, then use these as inputs to the metan command in order to do the meta-analysis and display the results. I'm sure that a Stata Journal article giving a practical example of this would be useful - over to you!

Best wishes

Jonathan

--On 21 December 2006 08:02 -0500 Austin Nichols <[email protected]> wrote:


Very helpful, thanks.  I look forward to your Stata Journal article.
Not to be a pest, but is there any chance you would add a sentence
discussing clustering to the help file (along with the three Hedges
references I supplied in my prior email)?  You could also suggest that
the approximate correction due to Kish (1965) gets you most of the way
to correcting for clustering in almost every case, e.g.
K=sqrt[1+r(b-1)] where b is the number of individuals per cluster (the
assumption of equal cluster size seems not so important as long as
there are no outliers) and r is the coefficient of intraclass
correlation (ICC), and SDcorrected=SD*K.  For that to work, of course,
you need to have not only sample size, but number of groups (e.g.
number of students and number of classes, or number of patients and
number of hospitals) for treatment and control in each study.

See page 162 and surrounding of
Kish, Leslie. 1965. Survey Sampling. New York, NY: John Wiley & Sons.

----------------------

Jonathan Sterne

Department of Social Medicine
University of Bristol
Canynge Hall
Whiteladies Road
Bristol BS8 2PR
UK

Tel:    0117 928 7396
Fax:    0117 928 7325
E-mail: [email protected]
web:    www.epi.bris.ac.uk/staff/jsterne.htm

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