I have an experimental treatment at 15 sites and would like to build models to associate usage rates of 4 species with a set of 6 explanatory variables. In the end, I would like to rank the importance of these variable for each species. Ordinarily, I would simply fit the models and then standardize the beta coefficient by dividing by the standard error and ordering by absolute value. However, in this case, I need to model a random effect of site and my response variable must be modeled as zero-inflated Poisson, which takes me outside of the realm in which I've seen this comparative analysis performed.
Is there an analogous procedure to ranking standardized beta coefficients for generalized linear mixed models?
Much thanks in advance!
Is it possible to rank standardized beta coefficients in generalized linear mixed models?