[R] nested random effects

[Berton Gunter]

I should have added that if you have only one Y observation per ID (within
family), then the ID variance component is residual error and the model
becomes (without any covariates)

Y~1, rand=~1|FAM

-- Bert


> On Wed, 2005-03-23 at 11:58 -0500, Shaw, Philip (NIH/NIMH) wrote:
> > Hi
> >  
> > I am struggling with nested random effects and hope someone 
> can help.
> >  
> > 
> > 
> > I have individuals (ID) who are nested within families 
> (FAM).  I want to
> > model an outcome variable, and take account of the 
> intercorrelation of
> > individuals within each family. 
> >  
> > I think this amounts to two random effects, one nested 
> within the other.
> >  
> > How can I model this in R?
> >  
> > So far I have tried using the library(nlme), and then
> >  
> > Y~ID, random=~1|ID*FAM, 
> >  
> 
> An interaction random effect/fixed effect is noted as 
> 
> random ~1|random/fixed
> 
> in your case random =~1|ID/FAM (but I don't uderstand why indiviuals
> withing families are fixed and and families are random, but there you
> go).
> 
> Check out Pinheiro and Bates Ch1, especially pg 23 onwards.
> 
> Cheers,
> 
> F 
> -- 
> Federico C. F. Calboli
> Department of Epidemiology and Public Health
> Imperial College, St Mary's Campus
> Norfolk Place, London W2 1PG
> 
> Tel  +44 (0)20 7594 1602     Fax (+44) 020 7594 3193
> 
> f.calboli [.a.t] imperial.ac.uk
> f.calboli [.a.t] gmail.com
> 
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