Once the Bayes factor is evaluated a decision theory approach to testing requires the specification of the prior odds (PO) on H0, PO = π0/(1 – π0), where π0 = Pr(H0), and the ratio of costs of type II to type I errors, R = CII/CI. The decision theory solution is to accept H1 if BF × PO < R. In contrast, frequentist hypothesis testing must specify the significance threshold α. The choice of PO and R is not straightforward, but at least it is clear what is being specified rather than having the implicit choices in a p-value threshold (Wakefield, 2009). To inform the choices, one may carry out simulations to examine the type I and type II errors associated with particular values of PO and R.
