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Technometrics Volume 38, 1996 - Issue 4
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Original Articles

Follow-Up Designs to Resolve Confounding in Multifactor Experiments

R. Daniel Meyer The Lubrizol Corporation, Wickliffe, OH, 44106
,
David M. Steinberg Department of Statistics and Operations Research Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Ramat Aviv, 69978, Israel
&
George Box Center for Quality and Productivity Improvement University of Wisconsin, Madison, WI, 53705
Pages 303-313 | Published online: 12 Mar 2012

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K. M. Eskridge, S. G. Gilmour, R. Mead, N. A. Butler & D. A. Travnicek. (2004) Large supersaturated designs. Journal of Statistical Computation and Simulation 74:7, pages 525-542.
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B. Abraham, H. Chipman & K. Vijayan. (1999) Some Risks in the Construction and Analysis of Supersaturated Designs. Technometrics 41:2, pages 135-141.
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R. Daniel Meyer & Robert G. Wilkinson. (1998) Bayesian variable assessment. Communications in Statistics - Theory and Methods 27:11, pages 2675-2705.
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Szu Hui Ng & Stephen E. Chick. (2004) Design of follow‐up experiments for improving model discrimination and parameter estimation. Naval Research Logistics (NRL) 51:8, pages 1129-1148.
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Chuen-Lung Chen, Rong-Ho Lin & Jianping Zhang. (2003) Genetic algorithms for MD-optimal follow-up designs. Computers & Operations Research 30:2, pages 233-252.
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Bruce E. Ankenman & Angela M. Dean. 2003. Statistics in Industry. Statistics in Industry 263 317 .
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Sharon P. Bocking, Sarah E. Steane, Sureeta Saini & Alan D. Bennett. 2001. Recombinant Protein Production with Prokaryotic and Eukaryotic Cells. A Comparative View on Host Physiology. Recombinant Protein Production with Prokaryotic and Eukaryotic Cells. A Comparative View on Host Physiology 319 329 .
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