Your response nicely clarifies a question that I've had for a long time, but which I've dealt with by giving each subject a unique label. Unless I'm missing something, both techniques should work as the toy example below gives exactly the same output in all 3 cases below (forgetting about the convergence problem). Would there be a reason to prefer labeling the levels one way or another or is it just a matter of convenience?
library(lmer) y <- rnorm(15) cond <- gl(3, 5, 15) obs <- gl(15, 1) subj <- gl(5, 1, 15) dd <- data.frame(y = y, cond = cond, obs = obs, subj = subj) l1 <- lmer(y~cond + (1|cond:obs), dd) l2 <- lmer(y~cond + (1|cond:subj), dd) l3 <- lmer(y~cond + (1|obs), dd) Douglas Bates a écrit: The difference between models like lmer(Glycogen~Treatment+(1|Rat)+(1|Rat:Liver)) and lmer(Glycogen~Treatment+(1|Treatment:Rat)+(1|Treatment:Rat:Liver)) is more about the meaning of the levels of "Rat" than about the meaning of "Treatment". As I understood it there are three different rats labelled 1. There is a rat 1 on treatment 1 and a rat 1 on treatment 2 and a rat 1 on treatment 3. Thus the levels of Rat do not designate the "experimental unit", it is the levels of Treatment:Rat that do this. -- Ken Knoblauch Inserm U371 Cerveau et Vision Dept. of Cognitive Neuroscience 18 avenue du Doyen Lépine 69500 Bron France tel: +33 (0)4 72 91 34 77 fax: +33 (0)4 72 91 34 61 portable: +33 (0)6 84 10 64 10 http://www.lyon.inserm.fr/371/ ______________________________________________ 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