 Staggered-level designs for response surface modelingHeidi Arnouts and Peter Goos () Working Papers from University of Antwerp, Faculty of Business and Economics Abstract: In industrial experiments, there are often restrictions in randomization caused by equipment and resource constraints, as well as budget and time restrictions. Next to the split-plot and the split-split-plot design, the staggered-level design is an interesting design option for experiments involving two hard-to-change factors. The staggered-level design allows both hard-to-change factors to be reset at different points in time, resulting in a typical staggering pattern of factor level resettings. It has been shown that, for two-level designs, this staggering pattern leads to statistical benefits in comparison to the split-plot and the split-split-plot design. In this paper, we investigate whether the benefits of the staggered-level design carry over to situations where the objective is to optimize a response, and where a second-order response surface model is in place. To this end, we study several examples of D-and I-optimal staggered-level response surface designs. Keywords: D- and I-optimality criterion; Cost; Response surface model; Split-plot design; Split-split-plot design; Staggered-level design (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ant:wpaper:2013027 Access Statistics for this paper More papers in Working Papers from University of Antwerp, Faculty of Business and Economics Contact information at EDIRC. |
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