mcfanda@gmail.com wrote:
I pushed a new master (0.9.7) with the last version of .nicifyTerm() as you suggested. In linux works well, it should be ok in other OS too.
Thanks once again for your software. I have a question regarding your calculation of CI for the multinomial regression. I am getting different 95% CI when I run your module vs. when I run the multinom regression in R and SPSS. I am using multinom function in r.
Hi, thanks for the suggestion. Do you have a working example that I can check? In the meantime, please consider that the way you compute the CI for glm() models may influence the results. GAMLj relies on R emmeans package, which does not necessarely uses the exact same approach of other packages.
To give you a concrete example, I've noticed myself that emmeans CI are different (not drammatically) from confint() function CI in logistic regression. I was puzzled and I asked the emmeans developers. Their swift reply was quite convincing. Maybe we are talking about something similar here. Please check out https://github.com/rvlenth/emmeans/issues/7
Hi, it's not clear to me how you would add factor loadinga to a mixed model. If you intend mixed SEM, they are not implemented in gamlj, and it would take a while before we do that. Almost certainly, they will be in a different module.