Hello folks,
Has anyone out there tried mimicking the ordinal logistic regression
results from the insomnia example given the second edition of Agresti's
book on Categorical analysis?
I was trying to learn to use the gllamm package for Stata using Agresti,
because his datasets are all on the web
http://www.stat.ufl.edu/~aa/cda/sas/sas.html
(and because I have the book).
As one might guess from the URL, SAS is the package he used to get the
results in his book.
I'm stuck trying to mimic table 12.7 on page 514, where he compares
estimates for a model using ordinal logistic regression (aka cumulative
logit) for some insomnia data (found in table 11.4 on p.462).
When I use Stata's ologit command to try to match his ML estimates, I
instead match his marginal GEE estimates.
If I try to mimic his use of ML random intercept models, using gllamm
using 'binomial' as the family and 'ologit' as the link, I get similar
but different coefficients.
Stata's ologit command matches his estimates for the mental impairment
example on page 279, so it cannot be that there is something which causes
the ologit and his ml cumulative logit models to be off all the time.
Is there any reason to worry about the slightly different results from
time to time? Does anyone know whether SAS computes these models
differently? Perhaps I'm missing a nuance about ML estimation vs. some
other method of fitting the models?
Any hints would be much appreciated,
Bill
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