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This paper develops a Bayesian approach for assessing equivalence andnon-inferiority hypotheses in two-arm trials using relative belief ratios. Arelative belief ratio is a measure of statistical evidence and can indicateevidence either for or against a hypothesis. In addition to the relative beliefratio, we also compute a measure of the strength of this evidence as acalibration of the relative belief ratio. Furthermore, we make use of therelative belief ratio as a measure of evidence, to assess whether a given priorinduces bias either for or against a hypothesis. Prior elicitation, modelchecking and checking for prior-data conflict procedures are developed toensure that the choices of model and prior made are relevant to the specificapplication. We highlight the applicability of the approach and illustrate theproposed method by applying it to a data set obtained from a two-arm clinicaltrial.

Bayesian Hypothesis Assessment in Two-arm Trials Using Relative Belief Ratios