lme vs lme4

Jim Maas <j.maas at ...> writes:

We are attempting to compare some results using lme and lme4.  I'm 
relatively new to this so could well be asking questions that are overly 
simplistic or naive, if so please inform.

We have an example that works with nlme(lme) and specifying the weights 
as the function varConstPower, however when we try to do a slightly more 
specific analysis using lme4(lmer) it doesn't seem to have the 
varConstPower function built it.  Is in nonsensical to build it into 
lme4?  It might well have some shortcomings/compromises. Is there a way 
we could accomplish the same thing with lme4 via some R coding or any 
other method?

It's not nonsensical, but it's way down the priority list for
the lme4 developer(s), so I wouldn't hold your breath.

  I guess my question would be: what are the advantages of lme4
for your particular analysis (i.e. reasons to use lme4 instead
of nlme)?  The main ones that I can think of are (1) speed and
(2) handling of crossed random effects.  For #1, you might consider
ASREML-R (I'm not particularly familiar with it, and I mostly
work with GLMMs, for which ASREML has some lacunae, but I've been
impressed by some of the posts at http://www.quantumforest.com/ ...)
For #2, it is *possible* [although clunky/slow] to implement crossed
random effects in (n)lme.

  See http://glmm.wikidot.com/faq#lme-comp (for example)