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Spatio-Temporal Methods in Environmental Epidemiology

Chapter 6 - Strategies for Modelling

Summary

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 procedures.
  • Model selection within the Bayesian setting and how the models themselves can be incorporated into the estimation
    process using Bayesian Model Averaging.
    • ©Gavin Shaddick and James V. Zidek 2015