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Outperforming Completely Randomized Designs

Outperforming Completely Randomized Designs

Publication:
Journal of Quality Technology
Date:
January 2004
Issue:
Volume 36 Issue 1
Pages:
pp. 12-26
Author(s):
Goos, Peter, Vanderbroek, Martina
Organization(s):
Katholicke Universiteit Leuven, Leuven, Belgium

Abstract

This abstract is based on the authors' abstract. Split-plot designs are frequently used in industry when factor levels are difficult to change or control. However, the resulting compound symmetric error structure affects estimation and inference procedures as well as the efficiency of the designs used. D-optimal first and second order split-plot designs are described that outperform completely randomized designs in terms of D- and G-efficiency. Use of these designs should be considered even when completely randomized designs are affordable.

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