Using the Bayesian information criterion to develop two-stage model-robust and model-sensitive designs.

Abstract

In this paper, we investigate use of the Bayesian Information Criterion (BIC) in the development of Bayesian two-stage designs robust to model uncertainty. The BIC is particularly appealing in this situation as it avoids the necessity of prior specification on the model parameters and can readily be computed from the output of standard statistical software packages.Bias; BIC; Design; Information; Integrated likelihood; Lack-of-fit; Model; Model-sensitive; Posterior probabilities; Prior probabilities; Probability; Software; Software packages; Two-stage procedures; Uncertainty;