Stop Treating Supersaturated Designs Like Other Screening Designs

• Activity Number: 200 - New Developments in the Design of Experiments
• Type: Contributed
• Date/Time: Tuesday, August 4, 2020 : 10:00 AM to 2:00 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Maria Weese* and Jonathan Stallrich and Byran JAY Smucker and David Edwards
• Companies: Miami University and North Carolina State University and Miami University (Ohio) and Virginia Commonwealth University
• Keywords: Dantzig selector; GO-SSD; Orthogonality; Power; Sparsity; Var(s+)

Abstract

The history of supersaturated designs is full of unrealized promise. Despite the vast amount of literature on supersaturated designs, there is a scant record of their use in practice. We argue this imbalance is due to the designs' inability to meet practitioners' analysis expectations and the existing literature's lack of clearly stated expectations. We tie exploration and optimization, two different goals of experimentation, to tradeoffs between power and type 1 error. The best strategy, which integrates a design's analysis with its construction, is shown to depend on the goal. Group orthogonal supersaturated designs (Jones et al. 2019), when paired with our new, modified analysis, are shown to have high power even with many active factors and so are recommended for more exploratory studies. Var(s+) designs (Weese et al. 2017), when paired with the Dantzig selector, are recommended as the initial experiment for optimization studies, as they can identify many active factors with a low type 1 error. The construction of both designs is less intuitive than traditional supersaturated designs and forces reflection on current best practices.