[R] lmer - BLUP prediction intervals

[Ben Bolker]

Daniel Caro <dcarov <at> gmail.com> writes:

> 
> Dear all
> 
> I have a model that looks like this:
> 
> m1 <- lmer(Difference ~ 1+  (1|Examiner) + (1|Item), data=englisho.data)
> 
> I know it is not possible to estimate random effects but one can
> obtain BLUPs of the conditional modes with
> 
> re1 <- ranef(m1, postVar=T)
> 
> And then dotplot(re1) for the examiner and item levels gives me a nice
> prediction interval. But I would like to have the prediction interval
> for the individual intercepts, not the conditional modes of the random
> effects, that is, the fixed effect (overall estimated intercept) + the
> conditional mode of the random effect (examiner or item level). Does
> this make sense? And if so, how would I calculate this? I'd like to do
> the same thing to obtain prediction intervals of individual growth
> rates in longitudinal models (i.e., overall growth rate + random
> effect).

  I think this belongs on the r-sig-mixed-models at r-project.org list.
Could you please re-post it there?  (I would redirect it myself but
am reading via gmane ...)  For a start, I would probably assume
independence of the uncertainty in the conditional modes and in the
overall slope parameter and compute the overall variance by adding the
variances ... ?  (Not sure that's right.)

  Ben Bolker