[R-sig-ME] Why || doesn't zero out the correlations in lmer

[ji@verissimo m@iii@g oii gm@ii@com]

You can also convert your factor to (three) numerical predictors,
according to its contrasts.
In that case, the double bar will remove the correlation parameters.

This is well explained by Reinhold Kliegl here:
https://rpubs.com/Reinhold/22193
João
On Fri, 2021-10-08 at 17:07 -0500, Simon Harmel wrote:
> Thank you, this is extremely helpful to know. You mentioned it's
> welldocumented, any possible links to share?
> Also, does nlme::lme() behave in the same manner in this regard?
> On Fri, Oct 8, 2021 at 4:46 PM Phillip Alday <me using phillipalday.com>
> wrote:
> > This is a well-documented issue: || doesn't zero correlations
> > between acategorical variable's levels. As far as I know, there
> > aresoftware-development/technical reasons for this, not statistical
> > ones.
> > The afex package has an implementation that zeroes everything out.
> > On 8/10/21 4:32 pm, Simon Harmel wrote:
> > > Dear Colleagues,
> > > I have a 'factor' predictor called 'type' (with 4 levels). In
> > > therandom part, I have used `||` so the levels of 'type' can't
> > > correlatewith each other.
> > > But I wonder why still correlations are reported in the
> > > output?Thanks, Simon
> > > lmer(y~type + (type || ID), data = data)
> > > Random effects: Groups   Name  Std.Dev. Corr ID     type0
> > > 0.4276          type1 0.7012   0.81          type2 0.7115   0.72
> > > 0.97          type3 0.7655   0.83 1.00 0.98
> > > _______________________________________________R-sig-mixed-
> > > models using r-project.org mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> > > 
> 
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