Screening Strategies in the Presence of Interactions

• Activity Number: 400
• Type: Contributed
• Date/Time: Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Angela Dean*+ and Danel Draguljic and David Woods and Susan Lewis
• Companies: The Ohio State University/Southampton University and Battelle Memorial Institute and University of Southampton and University of Southampton
• Keywords: Supersaturated designs ; Group screening ; factor selection ; interactions ; screening

Abstract

Screening is the process of using designed experiments and statistical analyses to search through a large number of potentially influential factors in order to discover the few factors that have a substantial effect on a measured response (i.e. that are "active"). In this setting, conventional fractional factorial experiments typically require too many observations to be economically viable. To overcome this problem in practice, interactions are often dropped from consideration and assumed to be negligible, sometimes without substantive justification. Such loss of information can be a serious problem in industrial experimentation because exploitation of interactions is a key tool for product improvement. This talk describes an assessment and comparison of two screening strategies for interactions, based on supersaturated designs and group screening, together with a variety of data analysis methods, using shrinkage regression and Bayesian methods. Recommendations on the use of the screening strategies are provided through simulation studies.