Hi,
I have a dataset with 12 ordinal variables of 4 categories. I use SEM command to perform CFA and to obtain goodness of fit indicators (Chi2, RMSEA, CFI, TLI, etc).

My model for analysis is:

sem (F1 F2 F3 F4-> p001 p002 p003 p004 p005 p006 p007 p008 p009 p010 p011 p012), difficult standardized
estat gof,stats(all)

(output omitted )
The iterations of this model are about 15 thousand. And my problem is that, Stata indicate "error r(430) convergence not achieved"

I know that this SEM command estimate a maximum likelihood model. That technique assumes that the observed variables are continuous and normally distributed. These assumptions are not met when the observed data are discrete (as occurs when using ordinal scales), thus significant problems can result when fitting CFA models for ordinal scales using ML estimation
(e.g., B. Muthe´n & Kaplan, 1985)

So, what command or option I should use or consider for calculate a gof indicators and CFA correctally??

Thanks for yours anwsers.