After looking at 48 glm binomial models I decided to try the quasibinomial
with the top model 25 (lowest AIC). To try to account for overdispersion
(residual deviance 2679.7/68 d.f.) After doing so the dispersion factor is
the same for the quasibinomial and less sectors of the beach were
significant by p-value. While the p-values in the binomial were more
significant for each section of the beach. -- telling me more about the
beach.
Is this ok? Can I just look at the binomial glm model 25 and look at its
p-values for beach sections and forget about the quasibinomial model 25?
J
Call:
glm(formula = cbind(Shells, TotalEggs - Shells) ~ Sector:Veg:Aeventexhumed,
family = quasibinomial, data = data.to.analyze)
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