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. Motivation: I'd like to use lmer instead of lme for fitting smoothing splines to longitudinal data. Cheers, Bert Gunter Genentech
Question about lrandom effects specification in lme4
2 messages · Bert Gunter, Douglas Bates
On Thu, Dec 4, 2008 at 6:21 PM, Bert Gunter <gunter.berton at gene.com> 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
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