[R-sig-ME] Random slopes for categorical variables

Timothy MacKenzie |@w|@wt @end|ng |rom gm@||@com
Wed Oct 6 05:39:17 CEST 2021


Sure, what if CAT has 2 levels, given R's default dummy coding, what
is the difference between (1 + CAT | ID) and (0 + CAT | ID), then?

On Tue, Oct 5, 2021 at 10:23 PM Phillip Alday <me using phillipalday.com> wrote:
>
> Yes.
>
> Well, to be more precise 0 + CAT and 1 + CAT estimate different
> contrasts and so the correlation you're estimating correspond to
> whatever contrast comes out.
>
> Same deal for 1 + CAT with sum vs treatment vs. Helmert coding.
>
> On 5/10/21 10:20 pm, Timothy MacKenzie wrote:
> > Hello All,
> >
> > I had a basic question. For continuous variables (X) killing the
> > intercept in the random part kills the correlation between random
> > effects (intercepts and slopes):
> >
> > (0 + X | ID)
> >
> > But for categorical variables (CAT) killing the intercept actually
> > allows for all levels of CAT (including the reference level) to be
> > correlated that is:
> >
> > (0 + CAT | ID) estimates more correlations than (CAT | ID)
> >
> > Am I correct?
> >
> > Thanks,
> > Tim M
> >
> > _______________________________________________
> > R-sig-mixed-models using r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >



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