Hi,
If you're running a loglinear model, there's usually no reason to use it
at all, because usually your data are, conditional on the categories,
independent. -robust- is useful when there's violation of assumption, eg
with overdispersion, heterogenous variance, and clustering. But it does
gives narrower results than is correct when N is small.
Hope that's all correct...
Tim
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Joan Holand
Sent: 30 January 2007 23:10
To: [email protected]
Subject: st: option -robust- for -glm- and -poisson-
Dear statalist,
I'm running a loglinear model (categorical data; Stata V.9, Windows XP)
using the -glm- (option: fam(pois)) and the -poisson- command.
I have a question about the option -robust-: When is it reasonable to
use this option? I have read that it makes the confidence intervall
narrower. Are there other reasons for / benefits of using this option?
Any comments would be appreciated!
Joan
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