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st: RE: cross-classified random effects


From   "Glance, Laurent" <Laurent_Glance@urmc.rochester.edu>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: cross-classified random effects
Date   Tue, 23 Mar 2004 07:05:19 -0500

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:phoenix@rand.org] 
Sent: Monday, March 22, 2004 6:42 PM
To: statalist@hsphsun2.harvard.edu
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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