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Staggered-Level Designs for Experiments With More Than One Hard-to-Change Factor

Summary: In many industrial experiments, some of the factors are not independently set for each run. This is due to time and/or cost constraints and to the hard-to-change nature of the levels of these factors. Most of the literature restricts 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 allow the less 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 less hard-to-change factors are reset whenever the most hard-to-change factors are reset. In this article, the authors 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. It is shown that the new designs are cost-efficient and that they outperform split-plot and split-split-plot designs in terms of the D- and A-optimality criteria. Because of the fact that the hard-to-change factors are independently reset alternatingly, the authors have named the new designs staggered-level designs. Supplementary materials for this article are available online.

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  • Topics: Design of Experiments
  • Keywords: A optimality, D-optimality, Split-plot design, Regression analysis, Linear regression, Least squares, Control factors, Constraints
  • Author: Arnouts, Heidi; Goos, Peter
  • Journal: Technometrics