I'm trying to fit a repeated measurement multivariate model in LME4.

Y = outcome
Y_index = index variable for Y, coding the 5 multivariate categories of Y
 X = time-invariant covariate (baseline)

Currently, my model looks like this:

M1 <- lmer (Y ~ ( -1 + Y_index + time + X ) + ( -1 + time | UserID) , data
= data )

(1) My first question is how to incorporate time-varying covariates. I find
no information about that in Dr Bates' (wonderful!) LME4 book, google
didn't help either. I have two covariates that

(2) Where can I find information about how to treat (highly skewed) ordinal
outcome variables in LME4? My outcome variables are ordinal, with the
values of
* 0 (not in the last weeks),
* 1 (2 days within the last week),
* 2 (4 days in the last week),
* 3 (nearly on all days in the last week),
and I'm currently treating them as continuous to simplify a bit. But I
should change that I guess.

(3) Is there any R literature for LME4 on multivariate modeling (tutorials,
instructions, guides, examples)? The things I found so far are either
covering multivariate multilevel models (like Hox 2010) without referring
to R at all, or they only talk about multivariate models in LME4 without
providing any syntax.
*
*
Thank you
Eiko

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