My independent variable is categorical, and my dependent variable is count. I have run a poisson log-linear generalized linear model which shows my independent variable is having a significant effect on my dependent. I now want to compare the categories to see if there are statistically significant differences in the count data between them. Does anybody know what test I can use here?
As far as I know, such post-hoc tests are essentially always Wald-z-tests of the coefficients in the suitably parametrized model (so that the coefficients represent the effect of the contrasts you want to test).
Hi Jochen Wilhelm thank you for your answer!
I am using SPSS and one of the output tables shows Parameter estimates. It shows the incidence rate ratio between the different categories of my independent variables and a p value for this (IRR). Is this what I'm looking for and so I don't have to do a seperate test?
I don't know SPSS. The IRR are usually the ratios of the rates of the group of interest and a reference group. So these tests give you at least all the comparisons to the reference group (if I am correct). I think there should be an EMMEANS (for Estimated Marginal MEANS) command in SPSS that will give you post hoc tests of different models.
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