Bivariate spline models to assess the joint effect of intensity and duration of alcohol drinking and cancer of the oral cavity: a focus on a novel approach

When modeling the relationship between a response and some continuous covariates, assuming linearity may be too restrictive in many contexts. Naive solutions to overcome this limitation, such as categorisation of the predictor, have well-known drawbacks. A viable alternative is represented by spline functions. In epidemiological studies, the number and position of knots usually have an important meaning. Therefore, special attention should be posed to techniques that allow to choose the number and position of knots. The aim of the present work is to: 1. introduce a two-step Bayesian procedure within the semiparametric generalised linear model framework to be applied in epidemiological studies where the effect of a continuous exposure on risk is under investigation; 2. show how this framework is applied in a bivariate context where the aim is to modeling the joint effect of intensity and duration of alcohol drinking in cancer of the oral cavity.