I am using a dirichlet-multinomial regression model. However I see that quite tidy associations for low-count categories don’t get picked up, essentially because the overall variance is quite high (I assume skewed by abundant categories).
For example (! I am plotting proportions here, but the data is actually in counts)
The yellow highlight category would rather seem associated with the x axis covariate.
I was wondering if anybody had experience with Dirichlet negative multinomial regression, where each category can have different overdispersions, but the counts across categories are correlated (sum to 100%)
Or even a simple Dirichlet negative multinomial would do
Any experience around?