Dear list,

I am would like to fit mixed model of the type:


y~b2[i]+(1|replication)

where y is my response measured at 16 different levels, b2[i] is a factor
describing the levels, and (1|replication) is a random effect describing
the replicates. I would like to quantify the difference between the various
levels of b2[i]. The sampling was repeated 6 times (16x6=96 observations).
Observations within each replicate are not independent, but I would like to
obtain a parameter estimate for each level. Is it correct to fit a model
like the abovementioned one? Basically, I want to address non-dependencies
within my data. To me it feels like that by modelling the various levels as
fixed factors, perhaps I do not need to include a random effect for the
replicated units.

thanks in advance,

Soner

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