st: Some additional questions regarding -gllamm, link (mlogit)-

[Andreas Schiffelholz <Andreas.Schiffelholz@gmx.de>]

Hi everyone,

Thanks a lot for the support I received so far, trying to understand the 
-gllamm- command in all its detail. I have three additional questions 
regarding options of the -gllamm- command when using it to calculate an 
multinomial logistic regression with random effects. I already consulted 
the manual as well as the book of Rabe-Hesketh and Skrondal (Volume II), 
but did not the options in all detail.
I'm working with a unbalanced panel dataset (x: companies; t:years) and 
two models, one with two, one with three (nominal) responses (basically 
one of the two responses of the first model is split into two different 
responses -> 3 responses). I calculate the ordinal models using a 
-logit, cluster (company)- approach for pooled and an -xtlogit, re 
vce(bootstrap)- approach for the random effects model. I want to 
calculate the nominal model in a comparable way. For the pooled model I 
use the -mlogit, cluster (company)- command. For the multinomial 
logistic regression with random effects I want to use a -gllamm- based 
model:
-gllamm varlist, i(Company) base(0) link(mlogit) cluster(Company) 
family(binom) nip(12) adapt trace-
In the documentation of gllamm several additional options are used. I do 
not fully understand if they are needed in my case (my goal is to stay 
as close and comparable to my -xtlogit, re vce (bootstrap)- approach as 
possible):
1. -expanded- is this option always needed for mlogit or only if there 
are different sets of alternatives? (In my dataset, the three 
alternatives are the same for every company in every year)
2. -nrf (...)- As far as I understand it the default is nrf(1), do I 
need more than one random effect?
3. -eqs (...)- To be honest, I do not fully understand this option, is 
it needed in my case?

Andreas
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