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 > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
