Fractions of Rechtschaffner matrices as supersaturated designs in screening experiments aimed at evaluating main and two-factor interaction effects Original Research Article

Optimal fractions of resolution V design matrices proposed by Rechtschaffner in 1967 are developed and applied as supersaturated designs in screening experiments. Rechtschaffner matrices allow evaluation of all main factors and two-factor interactions, which in many real-world studies are of practical significance. However, the number of experimental runs increases rapidly with the number of factors in the matrices, which are therefore impractical for more than 5–6 factors. On the contrary, saturated fractions based on Hadamard matrices, which are commonly applied in screening studies, cannot evaluate the interaction effects. Here, a procedure for selecting the optimum fractions of Rechtschaffner matrices is presented and provides supersaturated matrices that are well adapted to a variety of problems, thus allowing the development of screening studies with a relatively small number of experiments. The procedures developed to derive the size-reduced matrices and to evaluate the active factors are discussed and compared in terms of efficiency and reliability, by means of simulation studies and application to a real problem. These fractions are the first supersaturated design matrices capable of estimating interaction effects. Additionally, one important advantage of these supersaturated matrices is that they enable development of follow-up procedures in cases of inconclusive results, by enlarging the matrix and eventually resolving the full Rechtschaffner matrix of departure when it is necessary to evaluate the active factors and their interactions.