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Why we should be Bayesians (and often already are without realizing it) 

Why we should be Bayesians (and often already are without realizing it)
Chapter:
Why we should be Bayesians (and often already are without realizing it)
Author(s):

Neil Pearce

and Marine Corbin

DOI:
10.1093/med/9780199683901.003.0017
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date: 17 November 2017

Most epidemiologists write their Methods and Results sections as frequentists and their Introduction and Discussion sections as Bayesians. In their Methods and Results sections, they ‘test’ their findings as if their data are the only data that exist. In the Introduction and Discussion, they discuss their findings with regard to their consistency with previous studies, as well as other issues such as biological plausibility. This creates tensions when a small study has findings which are not statistically significant but which are consistent with prior knowledge or when a study finds statistically significant findings which are inconsistent with prior knowledge. Thus, in practice, almost all epidemiologists profess to be frequentists, but in practice are qualitative Bayesians. In some (but not all) instances, things can be made clearer if we include Bayesian methods are included formally in the Methods and Results sections of our papers and epidemiologists act as quantitative, as well as qualitative, Bayesians.

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