Staggered designs for experiments with more than one hard-to-change factor

Heidi Arnouts and Peter Goos ()

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

Abstract: In many industrial experiments, some of the factors are not independently reset for each run. This is due to time and/or cost constraints and to the hard-to-change nature of these factors. Most of the literature restricts the attention to split-plot designs in which all the hard-to-change factors are independently reset at the same points in time. This constraint is to some extent relaxed in split-split-plot designs because these require the least hard-to-change factors to be reset more often than the most hard-to-change factors. A key feature of the split-split-plot designs, however, is that the least hard-to-change factors are reset whenever the most hard to change factors are reset. In this article, we relax this constraint and present a new type of design which allows the hard-to-change factor levels to be reset at entirely different points in time. We show that the new designs are cost-efficient and that they outperform split-plot and split-split-plot designs in terms of statistical efficiency. Because of the fact that the hard-to-change factors are independently reset alternatingly, an appropriate name for the new design is staggered design.

Keywords: A- and D-optimality criterion; Cost; Hard-to-change factors; Split-plot design; Split-split-plot design; Staggered design (search for similar items in EconPapers)
Pages: 30 pages
Date: 2008-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:ant:wpaper:2008018

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