a month ago - last edited a month ago
I have a variety of related variables, the minority of which warrant analysis with a zero-inflated model. To facilitate presentation of test statistics and P-values, it would be nice if I could present results from the omnibus model and/or the main effects and their interaction for all variables. I'm posting this thread to see if that is possible with zero-inflated models. For this study, I measured vegetation on 3 locations over 2 months. Samples are independent across months and there are no repeated measures. I'm using the following code for this analysis:
proc genmod data=all;
class Location Month;
model AboveAvg = Location Month Location*Month/ dist=zinb;
When I include the class statement, test statistics and p-values correspond to pairwise comparisons with the variable level listed last in the dataset (top output, not complete but illustrates the point). When I omit the class statement, test statistics and p-values correspond to the variables and their interaction (bottom output), but all have 1 degree of freedom so I'm not sure if this is actually a measure of the main effects of Location and Month. Is it possible to test main effects or the omnibus model for zero-inflated models? Thank you for any help you can provide.