[R-sig-ME] Specifying and fitting LME model with unstructured error correlation within subject

[Clark Kogan]

Thierry,

I believe this will induce a compound symmetric covariance structure rather
than an unstructured covariance structure. I would like to allow for unique
correlations between different subtests.

Thanks,
Clark


On Sun, Dec 2, 2018 at 11:58 AM Thierry Onkelinx via R-sig-mixed-models <
r-sig-mixed-models using r-project.org> wrote:

> Dear Kogan,
>
> Add (1|id) as random effect. This will induce a correlation among the
> observations from the same individual.
>
> Best regards,
>
> ir. Thierry Onkelinx
> Statisticus / Statistician
>
> Vlaamse Overheid / Government of Flanders
> INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
> FOREST
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>
> Op vr 30 nov. 2018 om 18:20 schreef Kogan, Clark <clark.kogan using wsu.edu>:
>
> > I have some data where a number of individuals have taken a few different
> > subtests and there is 1 response per individual for each subtest. I am
> > fitting the following model using lmer:
> >
> > mod <- lmer(score ~ faculty + gender + subtest + gender:subtest +
> > faculty:gender + faculty:subtest+ (subtest|id), data = score)
> >
> > When fitting this model, I get the error:
> > Error: number of observations (=219) <= number of random effects (=219)
> > for term (subtest | id); the random-effects parameters and the residual
> > variance (or scale parameter) are probably unidentifiable
> >
> > The error makes sense to me - as there is only one data point for every
> > subtest*id, and so we cannot differentiate the random effects from the
> > residuals. What I would like to be able to do is specify that the
> residuals
> > have an unstructured correlation matrix within individuals to account for
> > the fact that an individual will likely have some correlation between
> their
> > subtest scores.
> >
> > Is there a way to do this in lmer or a similar package so that I can
> still
> > get Kenwood Rodgers or Satterthwaite corrected tests of effects (e.g.,
> with
> > pbkrtest or lmerTest).
> >
> > Thanks,
> > Clark
> >
> >
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