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
Is there any chance of development of multivariate linear mixed models for lme4
2 messages · Ian Dworkin, Andrew Robinson
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 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
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Andrew Robinson Department of Mathematics and Statistics Tel: +61-3-8344-9763 University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599 http://www.ms.unimelb.edu.au/~andrewpr http://blogs.mbs.edu/fishing-in-the-bay/