title: Fractional simplex designs for interaction screening in complex mixtures.
abstract: In mixture experiments, one may be interested in estimating not only main effects but also some interactions. Main effects and significant interactions in a mixture may be estimated through appropriate mixture experiments, such as simplex-centroid designs. However, for mixtures with a large number of factors, the run size for these designs becomes impractically large. A subset of a full simplex-centroid design may be used, but the problem remains regarding which factor-level settings should be selected. In this paper, we propose a solution that considers design points with either one or p individual nonzero factor-level settings. These fractional simplex designs provide a means of screening for interactions and of investigating the behavior of many-component mixtures as a whole while greatly reducing the run size compared with full simplex-centroid designs. The means of construction of the design arrays is described, and designs for < or = 31 factors are presented. Some of the proposed methodology is illustrated using generated data.
authors.affiliation: Department of Biology, University of Waterloo, Ontario, Canada. bjmcconk@sciborg.uwaterloo.ca
authors.forename: B J
authors.initials: BJ
authors.lastname: McConkey
authors.forename: P G
authors.initials: PG
authors.lastname: Mezey
authors.forename: D G
authors.initials: DG
authors.lastname: Dixon
authors.forename: B M
authors.initials: BM
authors.lastname: Greenberg
mesh_terms: D000465:Algorithms; D015233:Models, Statistical; D012997:Solvents; D013223:Statistics as Topic / Q000379:methods
chemical_list: D012997:Solvents