Empirical Bayes Methods, Evidentialism, and the Inferential Roles They Play

Empirical Bayes-based Methods (<i>EBM</i>) is an increasingly popular form of Objective Bayesianism (<i>OB</i>). It is identified in particular with the statistician Bradley Efron. The main aims of this paper are, first, to describe and illustrate its main features and, second, to locate its role by comparing it with two other statistical paradigms, Subjective Bayesianism (<i>SB</i>) and Evidentialism<i>. EBM</i>'s main formal features are illustrated in some detail by schematic examples. The comparison between what Efron calls their underlying "philosophies" is by way of a distinction made between confirmation and evidence. Although this distinction is sometimes made in the statistical literature, it is relatively rare and never to the same point as here. That is, the distinction is invariably spelled out intra- and not inter-paradigmatically solely in terms of one or the other accounts. The distinction made in this paper between confirmation and evidence is illustrated by two well-known statistical paradoxes: the base-rate fallacy and Popper's paradox of ideal evidence. The general conclusion reached is that each of the paradigms has a basic role to play and all are required by an adequate account of statistical inference from a technically informed and fine-grained philosophical perspective.