Models for count data

Logistic regression can handle only binary responses. If you have count data, such as the number of deaths or failures in a given period of time, or in a given geographical area, you can use Poisson or negative binomial regression. These data types are particularly common when working with aggregated data, which is provided as a number of events classified in different categories.

Poisson regression

Poisson regression models are generalized linear models with the logarithm as the link function, and they assume that the response has a Poisson distribution. The Poisson distribution takes only integer values. It is appropriate for count data, such as events occurring over a fixed period of time, that is, if the events are rather ...

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