Poisson and Ordinal Regression

This chapter explores two other regression models which are of considerable use in medical research: Poisson regression and ordinal regression . Poisson regression is an extension of logistic regression where the risk of an event to an individual is small, but there are a large number of individuals, so the number of events in a group is appreciable. The outcome for a Poisson model is a count of events in a group, usually over a period of time, for example number of deaths over 20 years in a group exposed to asbestos. The simplest way to check the model is to compare the observed values and those expected by the model. In the same way that the Binomial distribution defines the variance, so does the Poisson distribution. Tests are available for proportional odds but these tests lack power.