I am a student working on a research project and have a question/clarification regarding how to interpret the Fit Model output for a negative binomial regression. I am trying to predict a count variable (Variable A = how much time it took for an event to happen) based on sex (M vs F). I am using a negative binomial regression because my count variable is not normally distributed and my data is over-dispersed (I think this is the right approach but let me know your thoughts on this as well). My plan is to repeat this with different predictors and then include all the ones that are significant in a single model with multiple predictors.
When interpreting the report, my p-value for the Sex[F-M] term is significant, showing that sex is a predictor of Variable A. The generalized RSquare is very low so I know it's not a great fit.
--> I am trying to understand how to say that for a given sex (i.e. Females), Variable A is XX % higher (or lower). How do I do that?
--> How do I interpret the Estimate?
In the same report, I am also trying to look at Incidence Rate Ratios. If,
Level 1 = F, Level 2 = M, IRR = 1.303
--> Does that mean that for F compared to M, there is a 30% increase in Variable A?
Thanks for all the help and sorry if my explanation is not clear! I am just getting started with statistics...