[R-sig-ME] model building

[Davide Guido]

Hello Everyone!

I have a dataset with 150.000 statistical units (subjects) and 5 variables:

- Binary outcome (0/1) (y)
- municipality (string) (25 small areas)
- gender
- age
- copper concentration (in ppm) (25 level, one by municipality)

The last one, i.e. copper concentration, has been revealed per municipality 
(25 levels) and it is defined as municipalty mean of the different municipal 
sampling sites. I'm interested to the (conditional) copper effect on outcome 
and I have tried to specify this GLMM: 

gLMM <- glmer (y ~ gender + age + copper + (1 | municipality), family="
binomial", data=datiSM) 


Is it correct fit a model containing both disaggregated and aggregated 
variables? 

Unfortunately, I cannot measure the copper at disaggregated level (by 
subject). 

Thanks in advance

Davide