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st: gllamm help


From   Timothy.Mak@iop.kcl.ac.uk
To   statalist@hsphsun2.harvard.edu
Subject   st: gllamm help
Date   Tue, 2 Aug 2005 09:27:13 +0100

Hi stata list! (Sorry for reposting, cos last time it was in bad format 
plus it didn't have subject)

I've posted this question to allstat before and stata technical support, 
but received no answer. Don't know if you could help: 

Below is the question I posted: 

I have data collected across 4 sites and would like to perform a test to 
see whether the relationship between 2 binary variables, say A and B, 
differs between the sites. 

I think it makes sense to treat the sites as a random sample of sites, and 
thus use a random coefficient model with both random slope and intercept. 
Test would then be via a likelihood ratio test with the nested random 
intercept model (without the random slope). 

1st. My question is: Is this all good? 

Secondly, however, in one of the sites, the dependent variable (B) has 
only one value. So in normal (fixed-effects) logistic regression, this 
would be impossible due to the presence of empty cells. (In other words 
for both levels in A, the outcomes in B are entirely 0 in this particular 
site). 

Modelling using random slopes and intercepts won't give me an error 
message, but I wonder if the output is still valid. 

For your information, my entire dataset consist of 248 observations. THe 
smallest sites still have 28 observations. THe variable A has about half 0 
and half 1 in all sites. THe variable B has about 85% 0 and 15% 1 in all 
sites except the above. 

I used gllamm in STATA for the modelling. What struck me was that for the 
other sites, my unconditional log-odd-ratios (b1+u1) are (.000, .110, and 
.175), but for the site with a pure B variable, STATA gives me a 
log-odd-ratio of .888, considerably higher than the rest. 

****

And also another query: I've written an ado file that lets you draw line 
graphs easily, with dots representing means, and error bars and so on. 
What do I do if I want to share this with you guys? 

Thanks a lot. 

Tim
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