Hello,
I am fitting a multilevel logit model using runmlwin following the procedure explicated in LEMMA module 7. I read the guides but I have a doubt about the differences between the following two models:

Code:
runmlwin
y cons X Z,
level2(country: cons Z) ///
level1(id:) ///
discrete(distribution(binomial) link(logit) denominator(cons))
and

Code:



runmlwin



y cons X,



level2(country: cons Z) ///



level1(id:) ///



discrete(distribution(binomial) link(logit) denominator(cons))









I understood from the web that the standard procedure for random slopes is the first one, while the second explains the heteroskedasticity of between-country variations. However, is it possible to use the following specification for a random slope model?







Code:





runmlwin



y cons X X*Z,



level2(country: cons Z) ///



level1(id:) ///



discrete(distribution(binomial) link(logit) denominator(cons))





Shall I include a main Z effect into the code? From a theoretical point of view my variable Z should have no effect by itself on an individual level, though it represents a strong moderator for the effect of X.



Thank you for any help you could provide.