If the posterior deviance distributions for two different models overlap significantly, it is necessary to use additional criteria to compare model fit -namely a comparison of the relative complexity of the models. The Deviance Information Criterion (DIC) is perhaps the most general of such methods, being a generalisation of the Akaike information criterion for Bayesian hierarchical models [20] . We define the complexity of a model by its effective number of parameters, p D , defined as