I have a data set of repeated abundance counts over time. I am
investigating whether count data reduced to presence-absence (presence) data
will reveal similar population trends. I am using a negative binomial
distribution for the glm (package MASS) because the count data contains many
zeros and extreme values. "count" and "presence" are annual sums for each
metric. I have also included sampling effort (visits) as an independent
variable because sampling varies between 29-33 visits per year. My models
are:
glm.nb(count ~ year + visits) and
glm.nb(presence ~ year + visits)
I would like to test whether the coefficients for "year" are significantly
different between models. Please advise me on the best method to make such
a comparison.
Thank you,
Kayce
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