I have what should be a simple question about structure of the formula
for an lmer model. However, I can find no detailed description of how to
write multilevel nested formulas for lmer though so I need some advice.

Count data were collected at 10 subsample locations nested within each
of 7 general locations over a 20 year period of repeated measures. At
each of the 7 general locations there was a treatment applied partway
through the 20 year period to 1/2 of the subsample locations.

I thought running the lmer routine with the following general formula
setup would account for the fixed effects of the treatment and the
random effects of the nesting structure. A Quasipoisson distribution was
used to account for over/underdispersed data.

model1 <- lmer(count ~ a + (1 | b / c), dataset)

This model returns an error message though - "too many groups, only the
first is used".  I thought this formula should account for the grouped
and nested data structure. I have used this model structure with a
different dataset and a similar lmer model and it worked fine, nesting
the one explanatory variable within the other in the proper arrangement
and producing reasonable results. This time it does not work. Is there a
different way the formula should be set up?

Someone with more background in this method must have had a similar
problem before while using this lmer routine, so hopefully another
perosn on the list can describe/advise how to deal with this kind of
nested data and what may be the problem here...

 

Thank you,

Wayne Hallstrom

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