I have estimated a negative binomial model using the glm.nb function of MASS and discovered the following parameters Theta: 9.0487, S.E: 0.444
- Is it correct to assume that dispersion parameter has a standard deviation of 20.38?
- Does this value correspond to the Poisson overdispersion that is corrected by the negative binomial model or is my model still overdispersed?
- Joseph Hilbe states in his book that R's glm.nb function employs an inverted relationship of the dispersion parameter, theta. Thus a Poisson model results when theta approaches infinity. Suppose now that my second glm.nb model had estimates of Theta: 19.0487, S.E: 0.444. Would this model be less overdispersed than the first model?