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Optimal Split-Plot Designs

  • Peter Goos
Part of the Lecture Notes in Statistics book series (LNS, volume 164)

Abstract

Split-plot designs are heavily used in industry, especially when factor levels are difficult or costly to change or to control. This is because this type of design avoids too many changes of the whole plot factor levels, which leads to considerable savings in cost and time. The purpose of this chapter on split-plot designs is twofold. Firstly, we investigate to what extent the designs of Chapter 7 can be improved if the number of whole plots is increased. Secondly, we compare split-plot designs to completely randomized experiments in terms of D-efficiency. It turns out that the former are often more efficient than the latter.

Keywords

Design Point Efficiency Gain Candidate Point Plot Variable Plot Factor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Peter Goos
    • 1
  1. 1.Department of Applied EconomicsKatholieke Universiteit LeuvenLeuvenBelgium

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