[R] doing zero inflated glmm for count data with fmr
levyofi
levyofi at post.tau.ac.il
Mon Apr 20 15:23:41 CEST 2009
Hello R users,
Doing My PhD I collected count data which I believe is zero inflated. I have
run a statistical model with lmer and family=poisson and got
summary(model)@sigma=1 so I believe there is no overdispertion. I would
like to use the fmr function from the 'gnlm' library but I just cannot
figure out from the examples in the help page and some forums out there how
to convert the lmer parameters to the one used in fmr...
I have these variables in the model:
count: the number of logs in a foraging tray (this is the response
variable).
ta: the ambient temperature at the foraging tray.
habitat: the habitat type of the foraging tray.
season: the season in which the experiment session took place (summer or
winter).
moon: the moon phase (new or full).
position: a random factor (I had 4 foraging stations)
individual_id: a random factor indicating the individual foraged in the
tray.
This is the lmer parameters I have used:
model<-lmer(count~ta*habitat*season*moon + (1|individual_id) + (1|position),
data=countdata, family=poisson)
I would really appreciate the help. I love working with R and it really
changed the way I work with my data.
Thanks again,
Ofir.
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