Hierarchical Linear Model using lme4's lmer
On Sat, Jan 16, 2010 at 8:20 AM, Walmes Zeviani
<walmeszeviani at 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.