I'm having some problems getting my head around how MPLUS can be jigged to run a Seemingly Unrelated Oredered Probit. Suppose for simplicity's sake, I have two ordinal dependent variables "red" and "blue" that I wish to regress on co-variates "c1" and "c2"
I don't believe a model statement like this gives me what I need as it is the errors in the ordinal dependent variables that necessitate correlation:
red on c1 c2; blue on c1 c2;
Am I correct in this assumption?
What I am thinking might be a workaround is to designate red and blue as latent variables and then proceed with the estimation?
red on c1 c2; blue on c1 c2; f BY red@1 blue; f@1; [f@0];
where the residual covariance parameter is found in the free factor loading for blue.
ssp2yssp12 posted on Wednesday, August 08, 2012 - 8:20 am
Hello: I am running a seemingly unrelated ordered probit model, with two ordinal dependent variables. I have run various nonnested models and would like to compare them. Is there a particular model fit/goodness of fit statistic in the output that I should be looking at to compare models?