[R-sig-ME] Multivariate mixed models
j.hadfield at ed.ac.uk
Wed Oct 3 12:53:42 CEST 2012
The model cannot be fitted in lmer because a multivariate error
structure cannot be fitted. You can do it in asreml-R which I believe
is now free to academic users on windows.
Quoting "Ingleby, Fiona" <fci201 at exeter.ac.uk> on Sat, 22 Sep 2012
> Hi everyone,
> I have a dataset with 3 trait measurements for individuals from
> different families, like this:
> trait1 trait2 trait3 family
> 0.5 -0.2 0.2 A
> 0.2 0.7 -0.1 A
> 0.3 -0.3 0.5 A
> 0.1 -0.1 0.4 B
> -0.4 0.5 -0.6 B
> -0.1 0.8 0 B
> -0.2 0.7 0.5 C
> ...and so on (there are 80 families with 20 individuals measured from each).
> The model I want to fit is pretty straightforward, with the three
> traits as a multivariate response, and family as a random effect. I
> want to be able to extract the genetic variance-covariance matrix
> for the set of 3 traits. I can do this quite easily with MCMCglmm,
> and am aware of non-Bayesian methods in other programs (i.e. SAS),
> but awkwardly, I want to fit a non-Bayesian model in R.
> I can run individual lmer models for each trait, e.g.:
> model <- lmer (trait1 ~ 1 + (1|family) )
> and extract the random effects variance for the family term, giving
> me the genetic variance for each trait from each model individually.
> But this doesn't allow me to model the genetic covariance between
> traits, and so I'm wondering if there is a way to run lmer with a
> multivariate response, or if there is another method I could use to
> fit this kind of model?
> I did try re-arranging my dataset so that the 3 trait scores for
> each individual were stacked into one variable (creating new
> variables for trait.id (1, 2, or 3) and individual id within family)
> like this:
> trait.score trait.id individual family
> and then the model:
> model <- lmer (trait.score ~ 1 + (trait.id|family) + (individual|family) )
> but this model makes R crash and so I'm assuming there might be some
> kind of convergence problem?! And I'm not even sure this model would
> give me the genetic covariances between traits, it would probably
> just give the genetic variances for each trait (as before but in one
> model instead of 3 separately)?
> Any ideas/advice would be greatly appreciated.
> Fiona Ingleby
> R-sig-mixed-models at r-project.org mailing list
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