Yongtao Cao, Shaun S. Wulff, Timothy J. Robinson
Recent arguments have been made that optimal design criteria should incorporate pure error degrees of freedom for estimating unknown variance components. In this paper, we incorporate pure error, along with traditional design criteria, using Pareto optimization to identify a collection of optimal designs. This strategy demonstrates the trade-offs between these conflicting objectives without having to resort to weighted combinations of the criteria. The proposed approach also allows extension of the criteria for purposes of selecting optimal split-plot designs based on the D-criterion and pure error degrees of freedom.
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