Hi all, I have not used/looked at brms in years, and have a very simple/stupid question about posterior predictions from using the package that I have not been able to find an answer to elsewhere.

I have a model with the following form:

```
brm(bf(count ~ offset(LogOff)+X*Factor+(X*Factor|Species)+
(X*Factor|Species:Region),
zi~X*Factor+(X*Factor|Species)+(X*Factor|Species:Region),
family=zero_inflated_negbinomial(),
...
```

What I’d like to do is compare the posterior of the expected value across X and Factor, using something like `posterior_epred(mod, newdata , re_formula~(1+X*Factor|Species)`

.

What is not clear to me is whether the call to posterior_epred above is taking into the product of the zero inflated and NB components, which I’m looking for, or just the NB component)? I can also imagine interest in distinguishing between the two, and just for my own clarification, I assume this would be accomplished with dpar=“mu” or dpar=“zi”?

Apologies again for the very fundamental question, and thanks for any clarification.

John