[R-sig-ME] Modeling correlation structure in mixed models

[Phillip Chapman]

Hi All,

I have been trying to learn mixed models in R by reading the books by 
Pinheiro and Bates; Faraway (both linear models books); and Crawley (R 
Book), but I would appreciate some guidance from the more experience R 
users. (I have a fair amount of experience with mixed models in SAS.)

1. Is there another (other than the above) suggested reference for 
understanding the workings of the nlme and lme4 libraries?

2. Is it the case that lme accepts correlated structures ONLY in the 
error term? I have problems in which I would like model random effects 
(such as year) using a random term with an autocorrelated structure. In 
SAS I use options to the “repeated” statement to add correlation 
structure to the error term, and I use options to the “random” statement 
to give correlation structure to the other random effects. I haven’t 
found anything in lme or lmer that allows me to specify correlated 
random effects. gee only allows correlation structure in the error term 
and does not allow random effects.

3. All of the examples of random effects in lme seem to have nested 
error structures. Is it the case that lme does not allow crossed random 
effects? lmer allows much more flexible specification of random effects, 
but I don’t see anything that allows correlated error structures.

Thanks in advance,

Phil Chapman