Cross-level interaction specification in multilevel logit
Posted: Sat Dec 15, 2018 1:29 pm
Hello,
I have a rather stupid doubt that I could not solve on my own and I hope you could help me.
By reading the provided guides on multilevel modeling for binary responses I understood that the standard command for a multilevel model with random slope and random intercept would be:
however it is not yet clear to me what the following variation means in terms of equation:
Where z_3 is a contextual effect, say GDP and level 1 IDs are individuals. I could find that it is not a random slope model but it just models the heteroskedasticity, do you have any references for this kind of commands?
Finally, in the case of a cross-level interaction am I obliged to insert the main effect of z_3? would the following model have a random slope?
Thank you for any suggestion you could provide.
I have a rather stupid doubt that I could not solve on my own and I hope you could help me.
By reading the provided guides on multilevel modeling for binary responses I understood that the standard command for a multilevel model with random slope and random intercept would be:
Code: Select all
runmlwin y cons X_1 X_2 z_3, level2(country: cons X_1) ///
level1(id:) ///
discrete(distribution(binomial) link(logit) denominator(cons))
Code: Select all
runmlwin y cons X_1 X_2 , level2(country: cons z_3) ///
level1(id:) ///
discrete(distribution(binomial) link(logit) denominator(cons))
Finally, in the case of a cross-level interaction am I obliged to insert the main effect of z_3? would the following model have a random slope?
Code: Select all
runmlwin y cons X_1 X_2 X_1*z_3, level2(country: cons X_1 ) ///
level1(id:) ///
discrete(distribution(binomial) link(logit) denominator(cons))