Publication Cover
Journal of Quality Technology
A Quarterly Journal of Methods, Applications and Related Topics
Volume 36, 2004 - Issue 1
43
Views
38
CrossRef citations to date
0
Altmetric
Articles

Factorial Experiments When Factor Levels are Not Necessarily Reset

, &
Pages 1-11 | Published online: 16 Feb 2018

References

  • Anbari, F. T. (1993). “Experimental Designs for Quality Improvement when there are Hard-to-change and Easy-to-change Factors”. Ph.D. Dissertation. Drexel University.
  • Atkinson, A. C. and Donev, A. N. (1992). Optimum Experimental Designs. Oxford Science Publications. New York. NY.
  • Bingham, D. R. and Sitter, R. R. (2001). “Design Issues in Fractional Factorial Split-Plot Experiments”. The Journal of Quality Technology 33, pp. 1–15.
  • Ganju, J. and Lucas, J. M. (1997). “Bias in Test Statistics when Restrictions on Randomization are Caused by Factors”. Communications in Statistics—Theory and Methods 26, pp. 47–63.
  • Ganju, J. and Lucas, J. M. (1999). “Detecting Randomization Restrictions Caused by Factors”. Journal of Statistical Planning and Inference 81, pp. 129–140.
  • Ganju, J. and Lucas, J. M. (2000). “Analysis of Unbalanced Data from an Experiment with Random Block Effects and Unequally Spaced Factor Levels”. The American Statistician 54, 1, pp. 5–11.
  • Goos, P. and Vandebroek, M. (2001). “Optimal Split-Plot Designs”. Journal of Quality Technology 33, 436–450.
  • Ju, H. L. and Lucas, J. M. (2002). “Lk Factorial Experiments with Hard-To-Change and Easy-To-Change factors”. The Journal of Quality Technology, 34, pp. 411–421.
  • Kiefer, J. and Wolfowitz J. (1960). “The Equivalence of Two Extremum Problems”. Canadian Journal of Mathematics 12, pp. 363–366.
  • Kiefer, J. (1974), “General Equivalence Theory for Optimum Designs (Approximate Theory)”. Annals of Mathematical Statistics 2.
  • Littell, R. C.; Milliken, G. A.; Stroup, W. W.; and wolfinger, R. D. (1996). SAS System for Mixed Models. SAS Institute Inc. Cary. NC.
  • Lucas, J. M. (1999). “Comparing Randomization and A Random Run Order in Experimental Design”. AQC Annual Quality Congress Transactions, pp. 29–35.
  • Mood, A. M. (1940). “The Distribution Theory of Runs”. Annals of Mathematical Statistics 11, pp. 367–392.
  • SAS Institute (1997). SAS/STAT Software: Changes and Enhancement through Release 6.12. SAS Institute Inc., Cary, NC, pp. 571–701.
  • Searle, S. R. (1982). Matrix Algebra Useful for Statistics. John Wiley & Sons, Inc., New York, NY.
  • Searle, S. R.; Casella, G.; and McCulloch, C. E. (1992). Variance Components. John Wiley & Sons, Inc., New York, NY.
  • Trinca, L. and Gilmour, S. (2001). “Multistream Response Surface Designs”. Technometrics 43, pp. 25–34.
  • Webb, D. (1999). “Randomization Restrictions and the Inadvertent Split Plot in Industrial Experimentation”. Ph.D. Dissertation, Montana State University.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.