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

[Robert A LaBudde]

West et al. Linear Mixed Models. Chapman & Hall.

This text uses SAS, SPSS, HLM and R to set up and solve a variety of 
hierarchical mixed models. The text uses 'nlme' exclusively, but the 
related website has 'lme4' equivalent scripts.

At 06:42 PM 6/26/2009, Phillip Chapman wrote:

>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
>
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Robert A. LaBudde, PhD, PAS, Dpl. ACAFS  e-mail: ral at lcfltd.com
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