st: Syntax for contextual analysis of multilevel binary outcomes

[<Lori.Heise@lshtm.ac.uk>]

I am analysing a multi-stage cluster sample household survey of 5000 women in Peru and Brazil about experiences of domestic violence.  My outcome measure is current partner violence, coded as a binary variable.  I have a number of individual level exposure factors (e.g. education, alcohol use, child sexual abuse, etc), and cluster level factors created by aggregating the responses from individual women (for example, proportion of women in the cluster who completed secondary education or cluster mean on a scale of justifications of wife beating.  I want to analyse whether any of my cluster/community level predictors influence an individual woman's risk of experiencing partner violence, using multi-level analysis.
 
So far I have been using the following command syntax:  xi: xtmelogit  outcome exposure exposure || cluster:, var or
 
Can someone please clarify whether I should be putting the cluster level predictors in after the double bar or before?  It is my understanding that if I put them in after the bars then this gives me random coefficients and random intercepts.  Is there a way to set this up so it is just a random intercept model, and if so how? 
 
Also, how would I test/assess whether I need random coefficients to properly model the data?
 
Thanking you in advance.
 
Lori
 


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