[R-sig-ME] formula random terms in lmer function
Ben Bolker
bbolker at gmail.com
Thu Mar 6 19:01:14 CET 2014
On 14-03-06 10:23 AM, Senegaf wrote:
> Dear R-sig-mixed-models Group,
>
> I am new in R and I would confirm my understanding of lmer function in lme4 via the example below:
>
> lmer(Y~(1|X)+(1|X:Y)+(1|Y:Z))
>
> X is random
> The interaction between X and Y is random
> Z nested into Y is random
>
> If so, should I unsderstand that interaction and nesting are similarly specified.
See http://glmm.wikidot.com/faq#modelspec
There are no fixed effects in this model (although there is an
implicit intercept term).
X, X:Y, and Y:Z are *grouping variables*. X, Y, and Z will be treated
as categorical variables (factors); if this doesn't make sense (e.g. if
one of them is a numeric covariate with unique values for every
observation), then the model doesn't make sense. All three random effect
terms in the model (anything with a | in it is a random effect term) are
*scalar, intercept* random effects -- that is, the baseline/mean values
varies randomly among groups defined by the levels of X, X:Y, and Y:Z.
: denotes an interaction.
You could say that Y is *nested* in X, and you could specify the model
equivalently as
(1|X/Y) + (1|Y:Z)
I really don't know what you're trying to do without more context, but
it *might* be that you want (1|X/Y/Z) (Z nested within Y within X), or
equivalently (1|X) + (1|X:Y) + (1|X:Y:Z).
Hope that helps.
Ben Bolker
>
> Grateful if someone could advise. Thank you!
>
> Gaston
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