Please read ?lme carefully -- the info you seek is there. In particular, the weights argument for changing variance weighting by covariates and the correlation argument for specifying correlation structures.
Pinheiro and Bates's MIXED EFFECT MODELS IN S... is the canonical reference (which you should get if you want to use R as you said) that exposits the ideas at greater length. Bert Gunter Genentech Nonclinical Statistics -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Gareth Hughes Sent: Wednesday, June 27, 2007 7:50 AM To: r-help@stat.math.ethz.ch Subject: [R] lme correlation structures Hi all, I've been using SAS proc mixed to fit linear mixed models and would like to be able to fit the same models in R. Two things in particular: 1) I have longitudinal data and wish to allow for different repeated measures covariance parameter estimates for different groups (men and women), each covariance matrix having the same structure. In proc mixed this would be done by specifying group= in the REPEATED statement. Is this simple to do in R? (I've tried form=~time|indv/sex for example but this doesn't seem to do the job). 2) I've read that other correlation structures can be specified. Does anyone have any examples of how toeplitz or (first-order) ante-dependence structures can be specified? Many thanks, Gareth ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.