[R-sig-ME] Speed estimation for lmer?

[Adam D. I. Kramer]

Hi,

 	I'm about to estimate what I expect to be a fairly involved model,
like this one:

l <- lmer(y ~ x1*x2*x3 + (x1*x2*x3|grp) )

...the data set has 3,232,255 rows, for about 18000 grps, each of which has around
700 observations; x1, x2, x3 are continuous variables.

Is there any way I can estimate how long this run will take? Obviously this
depends on things like memory, processor, etc....but perhaps I could run it
on 5 groups and then multiply the amount of time it takes, or something like
that?

Also, given this information, is there some faster way to run the model? In
theory, I'd be interested in systematically checking which random effects I
could drop, but not if it would take weeks. Some prior posts to this list
(which I have only been actively reading since yesterday) suggest that lmer
is likely faster than lmer2, but there doesn't seem to be much discussion on
the speed of various modeling functions (lme, lmer, lmer2, glmer, glmmPLQ,
etc.).

Thanks in advance,
Adam Kramer