I'm conducting a zero-inflated Poisson regression using the pscl package in R. I've included interaction terms but am having an issue with interpretation. I am assuming an additive effect and summing coefficients (x + y + xy) but am not sure what to do about the confidence intervals or p-values. From what I understand, these have to be re-estimated, probably with some bootstrapping method, but I can't figure out how to do this.
The main issue is that one of my effects reverses in interaction. I've provided a simplified version of the code below (sorry, I can't share the data). Here's a brief description of the scenario: when doctors discuss re-injury prevention with their patients, time off work increases, but in interaction with a low-stress setting, it reduces time off work.
So my question is:
- How do you calculate interaction effect confidence intervals and p-values using a zeroinfl object?
- Is the process for calculating CIs and p-values different between the zero and count models?
Example code would be greatly appreciated!
model <- zeroinfl(TimeLoss ~ PrevDisc + LowStress + PrevDisc * LowStress, data = Doctors)