Equivalent factorial designs have identical statistical properties for estimation of factorial contrasts and for model fitting. Non-equivalent designs, however, may have the same statistical properties under one particular model but different properties under a different model. In this paper, we describe known methods for the determination of equivalence or non-equivalence of two-level factorial designs, whether they be regular factorial designs, non-regular orthogonal arrays, or have no particular structure. In addition, we evaluate a number of potential fast screening methods for detecting non-equivalence of designs. Although the paper concentrates mainly on symmetric designs with factors at two levels, we also evaluate methods of determining combinatorial equivalence and non-equivalence of three-level designs and indicate extensions to larger numbers of levels and to asymmetric designs. (c) 2007 Elsevier B.V. All rights reserved.
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Department of Mathematics, The Ohio State University, Mansfield, OH, 4906, Mansfield CampusDepartment of Mathematics, The Ohio State University, Mansfield, OH, 4906, Mansfield Campus
Katsaounis T.I.
Dingus C.A.
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Battelle Memorial Institute, Columbus, OH, 43215Department of Mathematics, The Ohio State University, Mansfield, OH, 4906, Mansfield Campus
Dingus C.A.
Dean A.M.
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Department of Statistics, The Ohio State University, Columbus, OH, 43210Department of Mathematics, The Ohio State University, Mansfield, OH, 4906, Mansfield Campus