Multivel ordered modeling for longitudinal data

[PRIVARD BRIN]

Hi all,

I am looking for a way to do multilevel-ordered modeling for longitudinal data.

I have 3-level for ordinal weighted logit models.
ndeed, my dependent variable has a score between 0; 0,25; 0,50; 0,75; 1 and because I would like to capture both individual and group effects.
This data set consists of 60 individual responses (level 3) nested in 20 group (level 2), for 4 different sector (level 1), in repeated 11 times. We have definitively 660 observations at level 3, 220 at level 2 and 44 at level 1

II understand that I have to run a multilevel ordinal logistic regression.
I found the commands ologit, meologit, gllamm following the examples of Sophia Rabe-Hesketh and Anders Skrondal (multilevel and long ordinal responses). But, i use Stata 12 and the last two commands don't seem to work.

My question is:

- what command or procedure would be appropriate for fixed or random effects model estimation for this version of stata -stata 12.
- How to consider the longitudinal character of my dependent variable (which is of hierarchical character).
- At what point do you integrate the specific variables at level 1, 2 and 3

Thanks for your responses.

[Rich Goldstein]

-gllamm- should "work" using version 12; see http://www.gllamm.org/

why do you think it doesn't "seem to work"?

It is likely to be your best available option (though your N is small for that many random effects)

[PRIVARD BRIN]

Thanks for feedback,

Actually, I tested the ologit, meologit commands. The gllamm protocol seemed complex to set up. But, if it turns out to be the best option available, I'll go for it.
my N = 660 (individual) + 220 (group) + 44 (setor). I will test which model would be appropriate (fixed or random) by Hausman test or not?

Thank for responses;