I assume that your outcome variable is binary.
Gllaam will not handle cross-classified data structures. MLWIN can handle
cross-classified models, but the syntax for cross-classified models is not
well documented. I have found PROC GLIMMIX to work well with
cross-classified data structures. The best reference for PROC GLIMMIX is
SAS System for Mixed Models by Ramon Littell - available through the SAS web
site.
Larry
-----Original Message-----
From: Do, Phoenix [mailto:[email protected]]
Sent: Monday, March 22, 2004 6:42 PM
To: [email protected]
Subject: st: cross-classified random effects
Hello,
I am trying to model risk behaviors for IDUs. Since my data is hierarchical
in nature, I want to apply a multilevel model using gllamm.
My dataset consists of an unbalanced panel in which some
people are observed only once while others are observed 2 to
10 times. We want to account for "neighborhood"
characteristics so we have neighborhood level variables in
our model. So level 1 would be the individual level time
series data. Level 2 would be person level. Level 3 would be
the neighborhood.
However, these people move and are not necessarily in the
same neighborhood throughout our study.
I believe what I need to do is use a crossed random effects
model.
Can you do this in gllaam? And if so, how? I haven't been able to find any
reference to this in the manual.
Thank you for any help you can offer,
Phoenix
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