Bayes linear methods for grouped multivariate repeated measurement studies with application to crossover trials

Abstract

SUMMARY This paper offers a study in the application of Bayes linear methods. We outline a general approach to the analysis of mean effects for grouped multivariate repeated measurement studies, based upon partial belief specification. We suggest a method for coherent partial prior specification for such structures, based on moment evaluations for exchangeable data. We describe the general collection of interpretive and diagnostic tools termed ‘Bayes linear methods’, and suggest a simple criterion for trial design. The theory is illustrated by analysis of a crossover trial concerned with side effects of kidney dialysis.