Mon, 07/19/2010 - 06:35

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.

In practice however, Y and Z may be latent constructs, measured by several indicators. (in my example, Y and Z are depression and self-esteem, each measured by several strongly correlated indicators.)

As far as I know, currently no methods exist to combine the dynamic random effects and the latent constructs (at least not in an easy way / within the frequentist framework).

Therefore, my question is: does any of you have an idea if this is possible in any way and, if yes, how it could be implemented.

The easier problem can be rephrased as: how can Y_i = b_i * X_i with X and Y latent and b_i subject specific be modeled.

At the workshop of prof. Boker at the IMPS conference, this question was also raised (in a less clear way I must admit) and subject-specific moderators were mentioned as a possible way to do this.

Regards,

Bart

Hi Bart,

Yes, this is possible in OpenMx. I believe that Tim Brick is working on an article about this right now. I suspect that until the article is reviewed he may not wish to share his script. But perhaps he will chime in and let us know how he is progressing.

Dear Bart and Steve,

I have the same question. And since this post is rather old, I wonder if there was any progress? So far I constructed only models in SEM- but they never revealed results that fitted to earlier lme models. So I think it could be really improved by using a random term. If there is so, please let me know how to apply it!

Thanks a lot!