On Thu, Dec 4, 2008 at 6:21 PM, Bert Gunter <[EMAIL PROTECTED]> wrote:
> Folks: > Suppose I have 3 random effects, A,B, and C. Using the older lme() function > (in nlme) it was possible (using the pdMat classes) to specify that they are > uncorrelated with identical variances. Is it possible to do this with lmer? > My understanding is that if I specify them as > lmer( y ~ ... + (A|Grp) + (B|Grp) + (C|Grp)) > then they are uncorrelated but have different variances. That's correct. At present there isn't an easy way to do what you want to do but I am working on modifications that would allow such changes. You would need to define a new reCovFac (random-effects covariance factor) class. In this case it would be straightforward because the covariance factor for the combined terms is a multiple of the identity. If you are feeling adventurous contact me off-list and I will describe how I think this could be done using the code in the "allcoef" branch of the SVN tree at R-forge. Installing that branch is not for the faint of heart. It is seriously broken right now but I'm confident I'll get it all back together in the not-too-distant future. > Motivation: I'd like to use lmer instead of lme for fitting smoothing > splines to longitudinal data. > > Cheers, > Bert Gunter > Genentech > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.