Aha! Thank you, Terrence - this could well be the issue at hand. I really should have done my due diligence and checked the warnings before posting (apologies!). I don't get the same issue with my data, but fitting my models does return the following:
1: In lav_model_vcov(lavmodel = lavmodel2, lavsamplestats = lavsamplestats, ... :
The variance-covariance matrix of the estimated parameters (vcov)
does not appear to be positive definite! The smallest eigenvalue
(= 2.902788e-14) is close to zero. This may be a symptom that the
model is not identified.
Still, I suspect my models are correctly identified. I wrote them on the basis of results from both an EFA (fa) and an omega analysis, which were identical in structure. More importantly, they are grounded in theory and prior research, including outputs from the developers of the instrument I am analysing. With all that being said, it certainly is possible that the model is not identified.
Searching for other examples of where people have encountered the same warning in a similar context, I found this thread
. Do you think it is appropriate to implement the potential fixes suggested by the respondent? There is more discussion of the same warning here
, and seems you and Yves have dealt with it in the context of EFAs here
. It appears in this tutorial
too. I am still a bit unsure of how to proceed in my case, however - any advice would be greatly appreciated.
If you think it would help, I can send you my deidentified dataset - it seems that using reproducible ones can create different issues!