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Biometrika 1993 80(1):39-59; doi:10.1093/biomet/80.1.39
© 1993 by Biometrika Trust
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Bayes linear methods for grouped multivariate repeated measurement studies with application to crossover trials

MALCOLM FARROW1 and MICHAEL GOLDSTEIN2

1School of Computing and Information Systems, University of Sunderland Priestman Building, Green Terrace, Sunderland SRI 3SD, U.K.
2Department of Mathematical Sciences, University of Durham Science Laboratories, South Road, Durham DH1 3LE, U.K.

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.

Key Words: Bayes diagnostics • Belief transform • Crossover trial • Exchangeability • Bayes linear methods • Optimal design


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[Abstract] [PDF]


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