Robert U <tacsunday <at> yahoo.fr> writes: > > Dear > R-users, >
[snip] This question probably belongs on r-sig-mixed-mod...@r-project.org . Followups there, please. > Let's say that I have 2 random effects, A (e.g. species, k=2) and B (e.g. individuals, n=100). I made some research about model syntax, and I have the understanding that everything at the left side of the random parameter is about SLOPE and everything at the right side about intercept : You really can't practically fit a random effect to 2 species (see http://glmm.wikidot.com/faq#fixed_vs_random > + (1 |B) > would give me an intercept per individual. > + (1 |A) > would give me an intercept per species. yes > + (1 |A:B) > would give me an intercept per individuals with nested effect (individual > inside species) This would be the same as (1|B) if the individuals are uniquely identified. Otherwise you probably want (1|A/B) [except that you can't really fit a random effect for k=2, as discussed above] > I would like to have random slopes per species. So I thought I > could do something like that : Probably not feasible. > + (A |B) so to have an intercept per individual and a slope value > per species. Graphically, I would therefore obtain 100 lines with > 100 different intercepts and 2 possible slopes (1 per > species). However, when I extract random parameter values (ranef()), > I have : what variable is your slope with respect to? Suppose it's time. Then I would recommend ~ A*time + (1|A:B) which will fit a (FIXED effect) interaction between species and time (different slopes and intercepts for each species), and a random intercept per individual. ______________________________________________ R-help@r-project.org 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.