# Interpreting negative binomial regression output in R

I've got a question concerning a negbin regression: suppose that you have the following commands

require(MASS)
attach(cars)
mod.NB<-glm.nb(dist~speed)
summary(mod.NB)
detach(cars)


(note that cars is a dataset which is available in R) and don't care if this model makes sense. What I'd like to know is, how can I interpret the variable theta (at the bottom of the summary). Is this the shape parameter of the negbin distribution and is it possible to interpret it as a measure of skewness? I appreciate every thought!

• this is a better fit for cross validated. – Chase May 6 '11 at 15:17

If Y is NB with mean $\mu$ then $var(Y) = \mu + \mu^2/\theta$. Skewness would not be an appropriate interpretation, but the departure from $\theta= 1$ is often taken as "extra-Poisson" dispersion.