Trade-off sensitive experimental design: a multicriterion, decision theoretic, Bayes linear approach
Farrow, M.; Goldstein, M.
We show how mutually utility independent hierarchies, which weigh the various costs of an experiment against benefits expressed through a mixed Bayes linear utility representing the potential gains in knowledge from the experiment, provide a flexible and intuitive methodology for experimental design which remains tractable even for complex multivariate problems. A key feature of the approach is that we allow imprecision in the trade-offs between the various costs and benefits. We identify the Pareto optimal designs under the imprecise specification and suggest a criterion for selecting between such designs. The approach is illustrated with respect to an experiment related to the oral glucose tolerance test.
Farrow, M., & Goldstein, M. (2006). Trade-off sensitive experimental design: a multicriterion, decision theoretic, Bayes linear approach. Journal of Statistical Planning and Inference, 136(2), 498-526. https://doi.org/10.1016/j.jspi.2004.07.008
|Journal Article Type||Article|
|Deposit Date||Apr 26, 2007|
|Publicly Available Date||Feb 24, 2010|
|Journal||Journal of Statistical Planning and Inference|
|Peer Reviewed||Peer Reviewed|
|Keywords||Imprecise utility, Multi-attribute utility, Pareto optimality, Oral glucose tolerance test.|
Accepted Journal Article