I have ecological count data across 15 sampling sites. The count data has a Poisson distribution and I have included an offset for "area_searched", which is the m^2 of each sampling site as it varies slightly. I have repeated these measures over 3 time periods (Session_ID). I want to know how I can compare the counts between each of the sessions to each other rather than just the first session. Is it possible to use the
emmeans package to do this? If this is not correct, is there another method I can use to compare them between one another?
I initially ran this model with the function
manyglm() from the
mvabund package but it appears that the
emmeans package cannot handle this model - is this correct?
My model is:
model <- glm(count ~ Session_ID + offset(log(area_searched)), family = "poisson", data = countdata)
If I do
I am only able to compare 3 to 1 and Session 2 to Session 1. I get the following output:
Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -8.2622 0.1796 -46.002 < 2e-16 *** Session_ID2 0.2134 0.2304 0.926 0.354383 Session_ID3 -1.0929 0.3304 -3.308 0.000941 ***
I have used the
emmeans package with the following code but I am not sure if it is correct to use with
offset() in the model.
A <- emmeans(model, ~Session_ID) pairs(A)
I get the following output:
contrast estimate SE df z.ratio p.value 1 - 2 -0.213 0.230 Inf -0.926 0.6237 1 - 3 1.093 0.330 Inf 3.308 0.0027 2 - 3 1.306 0.313 Inf 4.178 0.0001 Results are given on the log (not the response) scale. P value adjustment: tukey method for comparing a family of 3 estimates