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A General Strategy for Analyzing Data From Split-Plot and Multistratum Experimental Designs

Summary: Increasingly, industrial experiments use multistratum designs, such as split-plot and strip-plot designs. Often, these experiments span more than one processing stage. The challenge is to identify an appropriate multistratum design, along with an appropriate statistical model. In this article, the authors introduce Hasse diagrams in the response surface context as a tool to visualize the unit structure of the experimental design, the randomization and sampling approaches used, the stratum in which each experimental factor is applied, and the degrees of freedom available in each stratum to estimate main effects, interactions, and variance components. Use of the approaches is illustrated on several responses measured in a large study of the adhesion properties of coatings to polypropylene. The article discusses quantitative, binary, and ordered categorical responses, for designs ranging from a simple split-plot to a strip-plot that involves repeated measurements of the response. The datasets discussed in this article are available online as supplementary materials, along with sample SAS programs.

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  • Topics: Statistics
  • Keywords: Lifetime data, Split-plot design, Regression analysis, Linear regression, Response surfaces, Linear models, Poisson distribution, Estimation, Visual methods
  • Author: Goos, Peter; Gilmour, Steven G.
  • Journal: Technometrics