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Factor Screening via Supersaturated Designs

In: Screening

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  • Steven G. Gilmour

    (University of London, School of Mathematical Sciences, Queen Mary)

Abstract

Supersaturated designs are fractional factorial designs that have too few runs to allow the estimation of the main effects of all the factors in the experiment. There has been a great deal of interest in the development of these designs for factor screening in recent years. A review of this work is presented, including criteria for design selection, in particular the popular E(s 2) criterion, and methods for constructing supersaturated designs, both combinatorial and computational. Various methods, both classical and partially Bayesian, have been suggested for the analysis of data from supersaturated designs and these are critically reviewed and illustrated. Recommendations are made about the use of supersaturated designs in practice and suggestions for future research are given.

Suggested Citation

  • Steven G. Gilmour, 2006. "Factor Screening via Supersaturated Designs," Springer Books, in: Angela Dean & Susan Lewis (ed.), Screening, chapter 8, pages 169-190, Springer.
    • Handle: RePEc:spr:sprchp:978-0-387-28014-1_8
    DOI: 10.1007/0-387-28014-6_8
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