Multistratum response surface designs

Technometrics

Volumn 43, Issue 1, 2001, Pages 25-33

  Trinca, Luzla A ^a   Gilmour, Steven G ^b  

^a SÃO PAULO STATE UNIVERSITY UNESP   (Brazil)

^b UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; POLYNOMIALS; RANDOM PROCESSES;

RESPONSE SURFACE DESIGNS;

STATISTICAL METHODS;

EID: 0035253190     PISSN: 00401706     EISSN: None     Source Type: Trade Journal    
DOI: 10.1198/00401700152404291     Document Type: Article

References (20)

1. Atkinson, A. C., and Donev, A. N. (1989), "The Construction of Exact D-Optimum Experimental Designs With Application to Blocking Response Surface Designs," Biometrika, 76, 515-526.
2. Bingham, D., and Sitter, R. R. (1999a), "Minimum-Aberration Two-Level Fractional Factorial Split-Plot Designs," Technometrics, 41, 62-70.
3. _ (1999b), "Some Theoretical Results for Fractional Factorial Split-Plot Designs," The Annals of Statistics, 27, 1240-1255.
4. Box, G. E. P., and Draper, N. R. (1987), Empirical Model Building and Response Surfaces, New York: Wiley.
5. Cook, R. D., and Nachtsheim, C. J. (1989), "Computer-Aided Blocking of Factorial And Response Surface Designs," Technometrics, 31, 339-346.
6. Draper, N. R., and John, J. A. (1998), "Response Surface Designs Where Levels of Some Factors Are Difficult to Change," Australian and New Zealand Journal of Statistics, 40, 487-495.
7. Edmondson, R. N. (1991), "Agricultural Response Surface Experiments Based on Four-Level Factorial Designs," Biometrics, 47, 1435-1448.
8. Ganju, J., and Lucas, J. M. (1997), "Bias in Test Statistics When Restrictions in Randomization Are Caused by Factors," Communications in Statistics - Theory and Methods, 26, 47-63.
9. _ (1999), "Detecting Randomization Restrictions Caused by Factors," Journal of Statistical Planning and Inference, 81, 129-140.
10. Gilmour, S. G., and Trinca, L. A. (2000), "Some Practical Advice on Polynomial Regression Analysis From Blocked Response Surface Designs," Communications in Statistics - Theory and Methods, 29, 2157-2183.
11. Huang, P., Chen, D., and Voelkel, J. O. (1998), "Minimum-Aberration Two-Level Split-Plot Designs," Technometrics, 40, 314-326.
12. Ju, H. L., and Lucas, J. M. (1992), "Split Plotting and Randomization in Industrial Experiments," in Transactions of the 46th Annual Quality Congress, Milwaukee: American Society for Quality Control, pp. 374-382.
13. Kenward, M. G., and Roger, J. H. (1997), "Small Sample Inference for Fixed Effects From Restricted Maximum Likelihood," Biometrics, 53, 983-997.
14. Khuri, A. I., and Cornell, J. A. (1996), Response Surfaces (2nd ed.), New York: Marcel Dekker.
15. Letsinger, J. D., Myers, R. H., and Lentner, M. (1996), "Response Surface Methods for Bi-randomization Structures," Journal of Quality Technology, 28, 381-397.
16. Myers, R. H., and Montgomery, D. C. (1995), Response Surface Methodology, New York: Wiley.
17. Pearce, S. C. (1974), "Optimality of Design in Plot Experiments," in Proceedings of the 8th International Biometric Conference, Washington, DC: International Biometric Society
18. SAS Institute (1996), SAS/QC® Software: Usage and Reference, Version 6 (1st ed., vol. 2), Cary, NC: Author.
19. Schoen, E. D. (1999), "Designing Fractional Two-Level Experiments With Nested Error Structures," Journal of Applied Statistics, 26, 495-508.
20. Trinca, L. A., and Gilmour, S. G. (2000), "An Algorithm for Arranging Response Surface Designs in Small Blocks," Computational Statistics and Data Analysis, 33, 25-43.