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Stat Methods Med Res. 2010 Apr;19(2):107-25. doi: 10.1177/0962280208096688. Epub 2008 Sep 24.

Penalised regression splines: theory and application to medical research.

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  • 1Department of Mathematical Sciences, University of Bath, Bath, United Kingdom. g.marra@bath.ac.uk

Erratum in

  • Stat Methods Med Res. 2010 Jun;19(3):344.

Abstract

Generalised additive models (GAMs) allow for flexible functional dependence of a response variable on covariates. The aim of this article is to provide an accessible overview of GAMs based on the penalised likelihood approach with regression splines. In contrast to the classical backfitting, the penalised likelihood framework taken here provides researchers with an efficient computational method for automatic multiple smoothing parameter selection, which can determine the functional form of any relationship from the data. We illustrate through an example how the use of this methodology can help to gain insights into medical research.

PMID:
18815162
[PubMed - indexed for MEDLINE]
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