  In this paper, we review and apply several approaches to model selection for
analysis of variance models which are used in a credibility and insurance
context. The reversible jump algorithm is employed for model selection, where
posterior model probabilities are computed. We then apply this method to
insurance data from workers' compensation insurance schemes. The reversible
jump results are compared with the Deviance Information Criterion, and are
shown to be consistent.
