mcmcsamp error message...

Douglas Bates wrote:

On Wed, Aug 12, 2009 at 12:27 PM, Petar Milin<pmilin at ff.uns.ac.rs> wrote:

Hello!
I am puzzled with an error message that mcmcsamp for models with random
correlation parameters is not implemented yet. However, this would be the
case only with the model:
lmer(rt ~ FACTOR1 + COVARIATE1 + COVARIATE2 + COVARIATE3 +
(1+FACTOR1|subject) + (1|item) + (0+COVARIATE3|item), data=dat)
And same with:
lmer(rt ~ FACTOR1 + COVARIATE1 + COVARIATE2 + COVARIATE3 +
(1|subject) + (0+FACTOR1|subject) + (1|item) + (0+COVARIATE3|item),
data=dat)

If I run just:
lmer(rt ~ FACTOR1 + COVARIATE1 + COVARIATE2 + COVARIATE3 +
(1|subject) + (1|item) + (0+COVARIATE3|item), data=dat)
mcmcsamp ends fine.

I guess that the problem is in the fact that subjects were assigned
(randomly) to only one level of the FACTOR1. Am I right?

I'm not sure what you mean by "the problem". ?If FACTOR1 is a
non-trivial factor (i.e. it has more than one level) then the
random-effects terms (1 + FACTOR1|subject) and (0+FACTOR1|subject)
generate correlated random effects and currently mcmcsamp does not
handle models with correlated random effects.

If, as you say, each subject is assigned to only one level of FACTOR1
then neither of the terms above make sense. ?You can't expect to
estimate an interaction of FACTOR1 and subject when FACTOR1:subject is
equivalent to subject.

Sorry, I meant SOME subjects, but not all of them. And FACTOR1 has two
levels, exactly. Hence, my question could be rephrased: if only subsample
repeated levels of FACTOR1, could that be treated as a case of correlated
random effects, in principle?

Thus, in future, with the implementation
solved, that could be handled as a regular/proper case?

I think, previously, mcmcsamp handled this kind of nesting, but I might
be
wrong.

It is weird structure, anyway. (I am just trying to help a colleague.)

Thanks for the answer.
Best,
PM