Dear Masca

You may want to look at this former thread.

http://r.789695.n4.nabble.com/Network-meta-analysis-varConstPower-in-nlme-td871197.html

Also, the MCMCglmm package can implement random-effects meta-analysis in a very flexible way.

You could do some Google search for this (several former threads exist), if you are interested (or email me).

Best wishes,

Shinichi

On 1/03/2013, at 10:14 PM, "Masca, Nicholas" <nm180@leicester.ac.uk<mailto:nm180@leicester.ac.uk>> wrote:

Hi all,

In contrast to a typical standard error weighted, random-effects meta-analysis of study-level summary statistics, e.g. combining betas and their standard errors using "centre" as a random effect, I would like to fit a model where "centre" is nested within "country".  Does anyone know if it is possible to fit such a model using nlme (or a different R package)?

I tried searching for a solution to this problem in the archives and the only relevant posts I could find (from several years ago) suggested it could not currently be done in R.  I find this a little surprising, as the principle seems relatively straightforward given the flexibility of the nlme package (although I admit I do not fully understand how a "conventional" random-effects meta-analysis works, with only one observation/ treatment effect estimate from each centre [i.e. how is the residual estimated?]; if anyone has a good reference for this or wouldn't mind explaining it, I'd be very grateful!).

Thanks in advance.

Nick


Nick Masca, PhD
Medical Statistician
Cardiovascular Research Centre (3rd floor)
Biomedical Research Unit
Cardiovascular Sciences
University of Leicester
Tel: +44 (0)116 204 4776


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Shinichi Nakagawa, PhD
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