[R-sig-ME] Is there any chance of development of multivariate linear mixed models for lme4

Andrew Robinson A.Robinson at ms.unimelb.edu.au
Fri Feb 2 00:31:28 CET 2007

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!



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 if this is
> not the appropriate place for this.
>   I am in the process of making the transition from SAS to R. One of
> the major procedures I use(d) in SAS was PROC MIXED, and I am slowly
> 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 methods tend
> to be less useful. Not that PROC MIXED does this very effectively, but
> you can trick MIXED to do some multivariate models using the repeated
> 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
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

Andrew Robinson  
Department of Mathematics and Statistics            Tel: +61-3-8344-9763
University of Melbourne, VIC 3010 Australia         Fax: +61-3-8344-4599

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