-----Original Message-----
From: r-sig-mixed-models-bounces at r-project.org
[mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf
Of Andrew Robinson
Sent: Thursday, February 01, 2007 6:31 PM
To: Ian Dworkin
Cc: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] Is there any chance of development
ofmultivariate linear mixed models for lme4
Hi Ian,
I've been able to trick lme() into fitting multivariate
mixed-effects models, and I don't think that I relied on any
functionality that is not available within lmer at the
present. I can send you what I did if you're interested. I
wrote it up in:
Robinson, A.P., 2004. Preserving correlation while modelling diameter
distributions. Canadian Journal of Forest Research 34, 221--232.
Mind you, the code was ugly and not terribly intuitive!
Cheers
Andrew
On Thu, Feb 01, 2007 at 05:59:54PM -0500, Ian Dworkin wrote:
Hi,
From what I gather this is a list primarily dedicated to the
development of mixed model libraries for R. So I apologize
not the appropriate place for this.
I am in the process of making the transition from SAS to
the major procedures I use(d) in SAS was PROC MIXED, and I
getting familiar with lmer.
I was wondering if there is any discussion of working on the
development of multivariate mixed models? Most of the data I am
interested with is multivariate in nature, and univariate
to be less useful. Not that PROC MIXED does this very
you can trick MIXED to do some multivariate models using
statement and specifying an unstructured covariance matrix etc..
However the code is ugly and not very intuitive.
Anyways, I am asking in the vain hope that something is being
developed in lme4 for multivariate models.
Thanks
Ian