[R] nlme & lme for complex mixed ANOVAs

[David Airey]

Dear List,

I downloaded R for the first time yesterday, in the hopes that I might 
deal more effectively with a complex repeated measures experimental 
design involving inbred strains of laboratory mice. The design below, 
somewhat simplified, cannot be computed with standard ANOVA, because 
something called the X'X matrix is too large. The design has the 
following factors:

Between-subject factors (levels):
	inbred mouse strain (20, "twenty")
	sex (2)
Animals:
	10 per sex*strain combination (400 total)
Within-subject factors:
	drug (3)
	trial set (4)
	stimulus characteristic 1 (2)
	stimulus characteristic 2 (2)

My question for the R community is, does R have in nlme or lme the 
ability to compute this problem on a typical desktop PC? In Stata, for 
instance, which has a matrix size limit of 11,000, the problem above 
will not fit, using standard ANOVA. Matrix size can be determined by 
listing all the terms of the full model and multiplying the levels of 
each factor withing a term and summing all terms. I said simplified in 
the first paragraph above, because if I include the day of drug 
challenge, the model oversteps the number of within-subject factors 
allowed. So, surprisingly to me, Stata/SE, which I bought for large 
data sets, is too small! Not that I don't like Stata, but I am annoyed 
that I must find another tool to use. I understand that SAS Proc Mixed 
will compute the problem, because it may handle the covariance matrix 
in some kind of piecemeal fashion (perhaps by animal but I've no 
confirmation of this, except that it zips through a comparable data set 
on someone else's computer). However, I am running Apple OS X and don't 
have SAS on my machine. I don't really understand what's going on 
underneath these programs respective hoods, but my question here is 
whether R computes mixed models in such a way as to require a matrix 
size like Stata or like SAS, when mixed models of this size are 
presented?

Sincerely,

-Dave