We sometimes want to estimate models of count outcomes. Depending on substantive assumptions, we can model these using a linear model, an ordered outcome model, or a count-specific model. This tutorial talks about count models, specifically poisson models and negative beta binomial models.
Poisson models can be estimated using R's base glm
function, but negative beta binomial regression requires teh MASS add-on package, which is a recommended and therefore is pre-installed and you simply need to load it.
# poisson(link = 'log')
library(MASS)
# glm.nb()