Hi everyone,

 

I sent the message below to the R-help list, so apologies for
cross-postings.

 

Cheers,

 

Kris

 

________________________________

From: Kris Jamsen 
Sent: Wednesday, 17 September 2008 1:01 PM
To: 'r-help@r-project.org'
Subject: GLMMs



Hi everyone,



I'm trying to fit a generalized linear mixed effects model (logistic) in
R and am having some trouble specifying the covariance structure for the
random effects.  I'm using glmer, which by default assumes an
unstructured relationship between the random effects, but I want the
structure to be a multiple of an identity.  Here is my code:



glmer(y ~ 1 + (x1 + x2 + x3 + x4 -1 | group_id), family=binomial, ...)



where x1-x4 are the columns of my design matrix for the random effects.
group_id is the clustering variable.



The code above returns separate variances for the random effects
associated with x1-x4, as well as the correlation between them.  What I
really want is the random effects to all have the same variance (i.e.
multiple of an identity).  It doesn't seem that you can use the pdMat
classes, like with lme.  Can glmer do what I need it to do, or is there
another command that I should be using?



Any guidance would be great.  



Cheers,



Kris



Kris Jamsen

Research Fellow 

Centre for Molecular, Environmental,

Genetic and Analytic (MEGA) Epidemiology

Level 1, 723 Swanston St

The University of Melbourne

Victoria, 3010

AUSTRALIA



Email: kmjamsen@unimelb.edu.au <mailto:kmjamsen@unimelb.edu.au> 

Ph: +61 (0)3 8344 0700

Fax: +61 (0)3 9349 5815




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