ASQ

Exclusive Content & Downloads from ASQ

Practical Inference from Industrial Split-Plot Designs

Summary: [This abstract is based on the authors' abstract.]When factors are not reset independently in industrial response surface experiments, the observations in the resulting split-plot experimental design are often correlated. Often the data is analyzed as if the experiment was completely randomized and the model is estimated using ordinary least squares. A proper analysis of the experimental data requires a mixed model analysis involving generalized least-squares estimation. The differences in conclusions reach from the two methods are quantified to provide guidance for analyzing split-plot experiments in practice. Determination of denominator degrees of freedom for significant tests in mixed model analysis is also discussed.

Anyone with a subscription, including Site and Enterprise members, can access this article.


Other Ways to Access content:

Join ASQ

Join ASQ as a Full member. Enjoy all the ASQ member benefits including access to many online articles.

Subscribe to Journal of Quality Technology

Access this and ALL OTHER Journal of Quality Technology online articles. You'll also receive the print version by mail.

  • Topics:
  • Keywords: Degrees of freedom,Least squares,Residual analysis,Response surface methodology (RSM),Split-plot design
  • Author: Goos, Peter; Langhans, Ivan; Vandebroek, Martina
  • Journal: Journal of Quality Technology