[R-sig-ME] Why || doesn't zero out the correlations in lmer
me @end|ng |rom ph||||p@|d@y@com
Sat Oct 9 05:46:48 CEST 2021
On 10/8/21 17:07, Simon Harmel wrote:
> Thank you, this is extremely helpful to know. You mentioned it's well
> documented, any possible links to share?
The lme4 documentation, e.g.
> (Because of the way it is implemented, the ||||-syntax /works only for
> design matrices containing numeric (continuous) predictors/; to fit
> models with independent categorical effects, see |dummy
> or the |lmer_alt| function from the afex package.)
> Also, does nlme::lme() behave in the same manner in this regard?
I am unaware of nlme supporting the double-bar syntax at all, but
specifing the correlation structure to be diagonal (pdDiagonal? it's
been a while) will force all correlations to zero.
> 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 a
>> categorical variable's levels. As far as I know, there are
>> software-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 the
>>> random part, I have used `||` so the levels of 'type' can't correlate
>>> with 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
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