Hi All,
Can R perform sem models (with generalized outcomes; mine are binary) and give me some kind of model fit, such as something analogous to the RMSEA or CFI that you'd get in sem with continuous outcomes?
I have four waves of data and I'm examining employment status and rearrest as endogenous outcome variables. I have built and run a generalized structural equation model (-gsem-) in stata. All is well with the model, except I can't evaluate the model as a whole. Of course there are smaller tests that compare models such as the AIC/BIC, likelihood ratio tests, Wald, but these only compare models as opposed to evaluating the fit.
So my questions are: (1) does R do gsem (non-continuous outcomes) and have a way of evaluating the overall model? (2) if it does not have a way of evaluating the model overall, what should I present in a report along with the obvious findings? and (3) anyone familiar with any papers that have used sem with generalized outcomes? I've searched and can't find any published or unpublished. I imagine looking at one and seeing what they report would be very helpful.
Thank very much.
Nate
OpenMx can handle ordinal data and reports RMSEA for these models.
It does so by modelling a normally distributed trait, plus thresholds on this to generate predicted values for your ordinal variables.
Here's a worked-through example of ordinal modelling in OpenMx
http://openmx.psyc.virginia.edu/docs/openmx/latest/Ordinal_Path.html