[R-sig-ME] Random-effects variance-covariance matrix in lmer?
m@tthi@s@suter m@iii@g oii @groscope@@dmi@@ch
m@tthi@s@suter m@iii@g oii @groscope@@dmi@@ch
Wed Oct 2 16:52:54 CEST 2019
Thanks, Philipp.
I was a aware of the pdDiag and the pdCorSym solution, and so I specifically asked for pdCompSym and pdIdent ...
As for your compound symmetry suggestion, it is not quite clear to me. Up to now, I would have named "(1|Worker:Machine)" a random interaction term, specifying a distinct level for each worker*machine combination (and that's what is given by ranef(m_cs). How does this relate to the covariance in the compound symmetry, where also a multiple of identity is fit to diagonal?
I have also tried to sort out the pdIdent equivalent, using similar coding as you suggest below, but was not successful so far. Do you know a similar solution?
Thanks again,
Matthias
-----Ursprüngliche Nachricht-----
Von: Phillip Alday <phillip.alday using mpi.nl>
Gesendet: Mittwoch, 2. Oktober 2019 16:30
An: Suter Matthias Agroscope <matthias.suter using agroscope.admin.ch>; r-sig-mixed-models using r-project.org
Betreff: Re: [R-sig-ME] Random-effects variance-covariance matrix in lmer?
This is a frequent question for lme4 and MixedModels.jl and the answer is....
it's not going to be supported in any mainstream release of either package in the foreseeable future.
You can however still get some of these structures by clever specification of the random effects.
For example:
data(Machines,package="nlme")
library(lme4)
m <- lmer(score ~ 1 + Machine + (0+Machine|Worker), Machines)
# with compound symmetry
m_cs <- lmer(score ~ 1 + Machine + (1|Worker) + (1|Worker:Machine),
Machines)
# pdDiag -- for continuous variables, you could just use the || syntax
m_diag <- lmer(score ~ 1 + Machine + (0+dummy(Machine,"A")|Worker) +
(0+dummy(Machine,"B")|Worker) + (0+dummy(Machine,"C")|Worker), Machines)
I'll leave pdIdent as an exercise for the OP. ;)
Best,
Phillip
On 02/10/2019 15:50, matthias.suter using agroscope.admin.ch wrote:
> Hi all
>
> I'm looking for a way to specify a more complex variance-covariance matrix for the random effects in lmer(). For example, in lme() (nlme package), there are the pdMat classes to specify e.g. a compound symmetry (pdCompSym) or a multiple of an identity (pdIdent) structure for the variance-covariance matrix of random effects. Is there a possibility to code an equivalent for lmer()? I'm specifically interested in "compound symmetry" and "multiple of an identity".
>
> I assume that Douglas Bates or Ben Bolker have a distinct answer on that.
>
> Thanks in advance,
> Matthias
>
>
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