On Sat, Jan 16, 2010 at 8:20 AM, Walmes Zeviani <walmeszevi...@hotmail.com> wrote: > > Doug, > > It appears you are mixing nlme and lme4 formulation type. > On nlme library you type > > lme(y~x, random=~1|subjetc) > > On lme4 library you type > > lmer(y~x+(1|subject)) > > You mixed them. > > At your disposal.
Which is what I tell my wife when I am standing by our sink. > Walmes. > > > Doug Adams wrote: >> >> Hi, >> >> I was wondering: I've got a dataset where I've got student 'project's >> nested within 'school's, and 'division' (elementary, junior, or >> senior) at the student project level. (Division is at the student >> level and not nested within schools because some students are >> registered as juniors & others as seniors within the same school.) >> >> So schools are random, division is fixed, and the student Score is the >> outcome variable. This is what I've tried: >> >> lmer(data=Age6m, Score ~ division + (1|school), random=~1 | school) >> >> Am I on the right track? Thanks everyone, :) >> >> Doug Adams >> MStat Student >> University of Utah Walmes is correct that this is mixing two formulations of the model. It turns out that the model will be fit correctly anyway. The lmer function has a ... argument which will silently swallow the argument random = ~ 1|school and ignore it. Looks like we should add a check for specification of a random argument and provide a warning if it is present. ______________________________________________ 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.