I have a zero-inflated negative binomial model. I have used incidence rate ratios and I'm trying to interpret the coefficients in relation to my predictors. Most of my predictors are continuous variables of census data — ie: % of the population that is Hispanic; % of the population less than age 18, etc. I know that the IRR is normally interpreted as the rate ratio for a 1-unit increase in the independent variable, but what does this mean in terms of these continuous predictors — does this mean the IRR is the estimated rate ratio for a 1% increase in % Hispanic. Is there a way I can scale this so it can be interpreted to be the estimated rate ratio for a 10% increase in the % Hispanic? Also, one of my IRR's is 20. Does that seem unusually high?
Solved – Negative binomial — IRR interpretation for predictors
incidence-rate-rationegative-binomial-distributionpredictive-models
Best Answer
Yes.
Divide the variable by 10 before you run your regression.