Searching for Powerful Supersaturated Designs

Abstract

An important property of any experimental design is its power, defined roughly as its ability to detect active factors. For supersaturated designs, power is even more critical. We consider several popular supersaturated design construction criteria in the literature, propose several of our own, and perform a simulation study to evaluate them in terms of power. We use two analysis methods—forward selection and the Dantzig selector—and find that, although the Dantzig selector clearly outperforms forward selection, there is no clear winner among the design construction criteria.

• Bayesian D-Optimal
• Dantzig Selector
• E(s²)
• Forward Selection
• Model Robust

Additional information

Notes on contributors

Maria L. Weese

Dr. Weese is an Assistant Professor in the Department of Information Systems & Analytics. She is a senior member of ASQ. Her email address is [email protected].

Byran J. Smucker

Dr. Smucker is an Assistant Professor in the Department of Statistics. His email address is [email protected].

David J. Edwards

Dr. Edwards is an Associate Professor in the Department of Statistical Sciences & Operations Research. He is a member of ASQ. His email address is [email protected].