Generalised additive models

Abstract

The issue concerning this chapter is that covariates need not enter a generalised linear model merely as linear terms. Quadratic and higher-order terms can sometimes be useful in explaining variation in the data. In this chapter nonlinearities are explored using several techniques; discretisation, polynomial regression, splines and generalised additive models. These methods are explored using a single example to highlight the advantages and disadvantages of each approach.