Three-level equivalent-estimation split-plot designs based on subset and supplementary difference set designs

Kalliopi Mylona, Harrison Macharia and Peter Goos ()

Working Papers from University of Antwerp, Faculty of Business and Economics

Abstract: In many industrial experiments, complete randomization of the runs is impossible as, often, they involve factors whose levels are hard or costly to change. In such cases, the split-plot design is a cost-efficient alternative that reduces the number of independent settings of the hard-to-change factors. In general, the use of generalized least squares is required for model estimation based on data from split-plot designs. However, the ordinary least squares estimator is equivalent to the generalized least squares estimator for some split-plot designs, including some second-order split-plot response surface designs. These designs are called equivalent-estimation designs. An important consequence of the equivalence is that basic experimental design software can be used for model estimation. We introduce two new families of equivalent-estimation split-plot designs, one based on subset designs and another based on supplementary difference set designs. The resulting designs complement existing catalogs of equivalent-estimation designs and allow for a more flexible choice of the number of hard-to-change factors, the number of easy-to-change factors, the number and size of whole plots and the total sample size. We show that the newly proposed designs possess good predictive properties when compared to D-optimal split-plot designs.

Keywords: Generalized least squares; OLS-GLS equivalence; Ordinary least squares; Response surface design; Split-plot design; Subset design; Supplementary difference set (search for similar items in EconPapers)
Pages: 29 pages
Date: 2011-07
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Journal Article: Three-level equivalent-estimation split-plot designs based on subset and supplementary difference set designs (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:ant:wpaper:2011010

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