Screening Strategies in the Presence of Interactions

Product and process improvement can involve a large number of factors which must be varied simultaneously. Understanding how factors interact is a key step in identifying those factors that have a substantial impact on the response. This paper assesses and compares screening strategies for interactions using supersaturated designs, group screening, and a variety of data analysis methods including shrinkage regression and Bayesian methods. Novel methodology is developed to allow application of Bayesian methods in two-stage group screening. Insights on using the strategies are provided through a variety of simulation scenarios and open issues are discussed.