Why || doesn't zero out the correlations in lmer
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 Jo?o
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 at 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
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