[R-sig-ME] Summarizing the fitted model takes more RAM than

[Gabor Grothendieck]

Note that the fitted method in lme had a level= argument that is no
longer available in lmer presumably because lmer does not assume
a hierarchy -- but do we have or will we have an easy way to get the
same effect as fitted(..., level=) in lmer?

library(nlme)
# example from plot.lme
fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject)

fit0 <- fitted(fm1, level = 0)
fit1 <- fitted(fm1, level = 1)

(Maybe this is a bad example since its actually not so hard:
   fitted(lmer(distance ~ age + (age|Subject), Orthodont))
gives level 1 and
  fitted(lm(distance ~ age, Orthodont))
gives level 0 but even here it involved the complexity of using different
approaches to get them whereas with lme one could do it in a
unified manner.)

On Mon, Dec 15, 2008 at 10:19 AM, Douglas Bates <bates at stat.wisc.edu> wrote:
> I believe you are using the terminology of multilevel modeling where
> one characterizes factors as being at the first level, the second
> level, etc.  One can fit multilevel models using lmer but one can also