Dropping correlations bet. random-effects in lme4 syntax
I have no idea what 0* means, but 0+ means "suppress the intercept" (which has knock-on effects for categorical variables and whether they're represented in the model as (nlevels-1) contrasts or nlevels). For the other things: try it out. The output of summary(m1) will show you which levels and correlations were kept.
On 03/10/2020 18:44, Simon Harmel wrote:
Thanks Phillip. What would be the meaning of placing `0 +` next to any
of the random effects (e.g., B) as shown in m2?
m1 <- lmer(y ~ A * B * C + (A * C | group) + (B|group) , data = data)??
m2 <- lmer(y ~ A * B * C + (A * 0+ B * C ?| group), data = data)??
On Sat, Oct 3, 2020 at 11:33 AM Phillip Alday <phillip.alday at mpi.nl
<mailto:phillip.alday at mpi.nl>> wrote:
You can split the specification of your grouping to achieve this, at
least in part:
lmer(y ~ A * B * C + (A * C | group) + (B|group) , data = data)
Note that life gets tricky with the interaction terms.
Phillip
On 03/10/2020 06:35, Simon Harmel wrote:
> Hello all,
>
> I know to drop all correlations among all level-1 predictors in
the random
> part of an lmer() call, I can use `||`. But I was wondering how
to drop
> correlations (a) "individually" or (b) "in pairs"?
>
> Example of (a) is how to drop the correlation of B with others
(A & C)?
> Example of (b) is how to drop the correlation between B and C?
>
> lmer(y ~ A * B * C + (A * B * C? || group), data = data)
>
> Thanks,
> Simon
>
>? ? ? ?[[alternative HTML version deleted]]
>
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