Comparing negative binomial models
Davg <davidgrimsey <at> hotmail.com> writes:
I am trying to compare negative binomial models for the prediction of sports games (I know that Poisson models would be better but I'm just trying Negative Binomial at the moment). But, to compare the models I need them to have the same theta value. How can I change the explanatory variables while maintaining the theta value?
library(MASS) modelfit <- glm(..., family=negative.binomial(theta=theta_value)) I believe that drop1() applied to a glm.nb() fit does this correctly (i.e. holds the theta parameter fixed at the estimate from the most complex model).