I would like to model the predictors of remaining married (dichotomous) in a variety of countries (categorical "place", n=9). I would rather not have a base, since it doesn't make sense to compare all of the other countries to what happens in, say, Tanzania. My current model therefore uses the prefix "ibn.":
Code:
logit married i.age5 i.dur5 i.kid4 i.repcat i.edu3 husedyn twotypes ibn.place, noconstant nolog or
I appreciate being able to follow this up with margins place and marginsplot so that I can make comparisons between countries. From other posts, I gather that I should interpret the output results from ibn.place as odds rather than odds ratios. Correct?

Another option would be to use melogit to create a generalized linear mixed additive model. This increases complexity but could account for variability within countries. I'm seeing errors when I try the following:
Code:
melogit married i.age5 i.dur5 i.kid4 i.repcat i.edu3 husedyn twotypes || place: , noconstant nolog or
"random effects level place is empty"

or
Code:
melogit married i.age5 i.dur5 i.kid4 i.repcat i.edu3 husedyn twotypes || i.place: , noconstant nolog or
or
Code:
melogit married i.age5 i.dur5 i.kid4 i.repcat i.edu3 husedyn twotypes || ibn.place: , noconstant nolog or
"factor-variable and time-series operators not allowed"

Would you please let me know how to create a generalized linear mixed additive model? I'll also appreciate your wisdom on what alternative approaches would add beyond a basic logit model with ibn.place. Thank you.