Mixed Effects and Nested Models

Hello,

I'm trying to understand the support OpenMx has for nested models and especially cross-classified models. I've found some great examples (http://psychological-research.org/R/) for doing these models in a wide data format. This approach though is a bit cumbersome for larger and more complex models, especially cross-classified models.

I can't find any examples using a multiple group approach (e.g. Muthen, 1994). Can OpenMx use this approach? Are there examples?

Dear all,

I was looking for a way to compute multilevel models in OpenMx, so I ported the Mx code in the appendix of Mehta & Neale's excellent paper (1) to OpenMx (2). As far as I'm aware, there is no working example of multilevel modeling in OpenMx yet, so I leave a link here in case someone is interested. Comments are welcome!

Chris

(1) Mehta, P. D., & Neale, M. C. (2005). People are variables too: Multilevel structural equations modeling. Psychological Methods, 10(3), 259–284.

(2) http://psychological-research.org/R/

Hi all,

I'm currently working on a cross-lagged mixed effects model of the following form:

Here, the "i" refer to random subjects and therefore we have subject-specific dynamic effects.
This model can be fitted with linear mixed modeling software, but this is only possible when Y and Z are measured.

Currently, is there any documentation on running a mixed effect or nested model? I know several people who are interested, but they need some information to get started. An example perhaps? (even a very simple one)