[R-sig-ME] P-values from interaction terms using lme4

Douglas Bates bates at stat.wisc.edu
Wed Aug 9 16:59:32 CEST 2017

On Wed, Aug 9, 2017 at 9:54 AM Phillip Alday <phillip.alday at mpi.nl> wrote:

> On 08/09/2017 04:46 PM, Douglas Bates wrote:

> > Technically it is true that the number of parameters does not depend on
> > the number of random effects, only on the number of unique values in the
> > covariance matrices for the random effects.  However, I think that leads
> > to an undercount of the effective number of parameters when, say,
> > performing a likelihood ratio test of models that differ in their random
> > effects specification.
> This is related to the more general issue of degrees of freedom in mixed
> models, right?


But in terms of estimation (especially as implemented in
> lme4/MixedModels.jl), increasing the levels of a random effect will
> generally provide better estimates, right?

Yes.  Or, to put it the other way, it is unrealistic to expect to obtain
precise estimates of variance components unless there is(are) a large
number of levels in the grouping factor(s) for the random effects.

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