R help - Dec 2008 - Question about lrandom effects specification in lme4

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

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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