Bayesian Model Criticism

We develop a framework for model criticism. Our approach is based on embedding a given model via the addition of an elaboration parameter. The value of an elaborated model is defined by the change in expected utility associated with updating the probability distribution on the elaboration parameter. This provides the experimenter with a numerical summary for model criticism. Our approach offers a unified framework for probing assumptions on which probability modelling is based. Model criticism is performed enterely within the Baysian framework. We explore relationships with other diagnostic measures, namely Fisher's score function, deviance and the Bayes factor