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.
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West, R.M. (2012). Generalised Additive Models. In: Tu, YK., Greenwood, D. (eds) Modern Methods for Epidemiology. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-3024-3_15
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DOI: https://doi.org/10.1007/978-94-007-3024-3_15
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