On 7/28/2015 3:05 AM, Göran Broström wrote:
On 28/07/15 08:33, Charlotte wrote:
Hello
I have count values for abundance which follow a pattern of
over-dispersal with many zero values. I have read a number of
documents which suggest that I don't use data transforming methods
but rather than I run the GLM with the quasi poisson distribution.
So I have written my script and R is telling me that Y should be more
than 0.
No, R is telling you that you must have 0 <= y <= 1 (see below).
For count data you should not use the binomial family, but rather
'poisson', or 'quasipoisson'.
With excess zeros, overdispersion is the symptom, but the quasipoisson
model is not the cure.
Even better than quasipoisson would be to use a ZIP (zero-inflated
poisson) model or a hurdle model to explicitly model the
excess zeros.
These are handled by the countreg package, at present only
available on R-Forge.
install.packages("countreg", repos="http://R-Forge.R-project.org";)
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