jamovi

Hi
covariates are indeed "their own distinct exogenous variables". For the statistical model any exogenous variable is a covariate, it's only the analyst that considers the variable a "covariated out" variable. This holds for multiple regression, ANOVA and path analysis as well. So, you are correct ...

Due to structural changes, jamovi version 2.6.* supports GAMLj3 up to version 3.6.1. Newer versions of GAMLj3 are available for jamovi 2.7.*. So please update jamovi to 2.7. If that is not an option, please remove GAMLj3 3..6.1 from your jamovi 2.6 and install version 3.6.1.

Due to structural changes, jamovi version 2.6.* supports GAMLj3 up to version 3.6.1. Newer versions of GAMLj3 are available for jamovi 2.7.*. We update the 2.6 library to offer GAMLj3 3.6.1. Thus, please remove GAMLj3 3..6.1 from your installation and install version 3.6.1

In any case, if you update to jamovi 2.7 it should be ok

Are you using GAMLj3 3.6.5 on jamovi 2.6.44? On 2.6.44 GAMLj3 3.6.1 should work fine

Hi
please be sure you're working with GAMLj3. Second, trying naming your cluster variable "Dyad_ID" and see whether the issue is solved.

What was the correspondence between lavaan and SEMLj?

HC3 is appropriated when you have issues with etheroschedasticity. Normality violation is better addressed with bootstrap methods. In general, what to do with assumptions violation really depends on which assumption is violated and how much the data depart from the assumption

that's usually a sign that the model did not converge or there are issues with convergence. Can you share a omv file to see the model?

I do not have access to Mplus (it's not open source). Did you try to check the results with R lavaan?