actually my biggest question is how to model the variables in amos to get accurate imputations. just allow all covariances and the impute? that seems logical.
To be honest, I haven't used AMOS much for creating imputed data sets. I usually use either R (most often) or sometimes SPSS. With that said, the way you went about it seems reasonable from what I read. I've also heard of people analyzing their imputed datasets in AMOS, by using the multi group analysis feature and specifying each group as one of their imputed datasets...
I don't have the SPSS missing values analysis add-on. Further, I have a very small dataset and it has been recommended to me that I use Bayesian imputation. To do so, I'm trying to use AMOS to create and save the MI dataset with 5 imputed datasets. I simply created 4 observed variables (those that I want to analyze) and then launched the imputation procedure in AMOS. Seems like I got the imputed datasets I was desiring, but I'm a little unsure. Any thoughts?