Spatio-Temporal Methods in Environmental Epidemiology
Chapter 6 - Strategies for Modelling
This chapter considers both some of the wider issues related to modelling and the generalisability of results and more
technical material on the effect of covariates and model selection. From this chapter, the reader will have gained an
understanding of the following topics:
Why having contrasts in the variables of interest is important in assessing the effects
they have on the response variable.
The biases that may arise in the presence of covariates and how covariates can affect
variable selection and model choice.
Hierarchical models and how that can be used to acknowledge dependence between observations.
There are issues with using p–values as measures of evidence against a null hypothesis.
Basing scientific conclusions on it can lead to non-reproducible results.
The use of predictions from exposure models including acknowledging the additional uncertainty
involved when using predictions as inputs to a health model.
Methods for performing model selection, including the pros and cons of automatic selection
Model selection within the Bayesian setting and how the models themselves can be incorporated
into the estimation process using Bayesian Model Averaging.