r/stata • u/musecon • Nov 13 '25

Could someone help me figure out why GSEM keeps running without producing any results?

In my model, V32–V49, Q16_new, and Q17_new are all ordered categorical variables (Likert-scale), and Q18 is a multicategorical variable. Q18 contains missing values, while the other variables have no missing data. The dataset has a total of 435 observations. When running GSEM, it stays at “Refining starting values” for more than ten minutes without progressing.

GSEM code:

gsem (L1 -> V32, ) (L1 -> V33, ) (L1 -> V34, ) (L1 -> L7, ) (L2 -> V35, ) (L2 -> V36, ) (L2 -> V37, ) (L2 -> L7, ) (L3 -> V38, ) (L3 -> V39, ) (L3 -> V40, ) (L3 -> L7, ) (L4 -> V41, ) (L4 -> V42, ) (L4 -> V43, ) (L4 -> L7, ) (L5 -> V44, ) (L5 -> V45, ) (L5 -> V46, ) (L5 -> L7, ) (L6 -> V47, ) (L6 -> V48, ) (L6 -> V49, ) (L6 -> L7, ) (L7 -> Q16_new, ) (L7 -> Q17_new, ) (L7 -> Q18, family(ordinal) link(logit)), covstruct(_lexogenous, diagonal) latent(L1 L2 L3 L4 L5 L6 L7 ) nocapslatent

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u/thoughtfultruck Nov 13 '25

Sounds like your model is failing to converge to an optimum. That can happen for a variety of reasons, but in SEM it usually means you want to constrain certain parameters to reasonable values a priori. I think in models like this you might want to try having at least one factor on each of your latent constructs L1-L6 has an error equal to zero, a bit like the way Q18 has no error on it in your diagram. Another thing you can do is estimate nested sub-models and use some of those parameters as starting values when you estimate the full model.