I'm trying to get the specification correct for a crossed and nested effect model. Suppose I want to cross `Sample`

& `typeStatus`

, and then have a random effect of `day`

nested within that cross?

I've been trying to figure it out from Ch2 (pdf) of the online book, *lme4: Mixed-effects Modeling with R*, but can't quite seem to get it.

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#### Best Answer

The pdf lists an example of fitting a model with crossed random effects using the `Penicillin`

dataset in section 2.1.2 (p. 4 of pdf), and an example of fitting a model with nested random effects using the `Pastes`

dataset in section 2.2.2 (p. 14 of pdf). At the beginning of the latter section, it reads:

Fitting a model with simple, scalar random effects for nested factors is done in exactly the same way as fitting a model with random effects for crossed grouping factors.

I don't know much about your data, but from these I would guess that you might specify your model like so:

`library(lme4) model = lmer(y ~ 1 + covariates + (1|Sample) + (1|typeStatus) + (1|day), data=myData) `

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