[R-sig-ME] glmer, split-plot design simple question
chico3 at sapo.pt
chico3 at sapo.pt
Fri Nov 30 20:33:41 CET 2012
Dear experts,
I have a question concerning the implementation of a mixed model in my
specific experiment. I have search the archives and found no answer to
my problem.
I have four luminaires randomly distributed. Two luminaires have light
on and two luminaires have no light. Below the luminaires I have two
treatments. Each treatment as four replicates that were randomly
distributed below the luminaires. Moreover, I have made all the
possible combinations of presence absence of light and treatments.
I want to check if there is a effect of each treatment and the
interactions between all the combinations.The response variable is a
proportion (number of specific specie/total number of species)
Treatment1<-as.factor(“Yes”,”No”)
Treatment2<- as.factor(“Yes”,”No”)
Light<- as.factor(“Yes”,”No”)
Response<-cbind(number_of_specific_species, total_species)
I have made this model,
model<-glmer(Response ~ Treatmen1*Treatment2 + (1|Light), family=binomial)
However this doesn´t allow to see the effect of light or the
interaction between light and treatments. Moreover, I don´t know how
to include overdispersion, since glmer doesn´t allow quasi families
such as glm.
I know this is a simple question, but I greatly would appreciate some
clues on how to proceed.
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