A mixed integer optimization approach for model selection in screening experiments. Issue 3 (27th May 2021)

• Record Type: Journal Article
• Authors: Vazquez, Alan R.; Schoen, Eric D.; Goos, Peter
• Is Part Of: Journal of quality technology. Volume 53:Issue 3(2021)
• Page Start: 243
• Page End: 266
• Publication Date: 2021-05-27
• Subjects: best-subset selection -- Dantzig selector -- definitive screening design -- sparsity -- two-factor interaction; Quality control -- Periodicals; Qualité -- Contrôle -- Périodiques; Quality control; Quality control; Periodicals; 620.0045
• DOI: 10.1080/00224065.2020.1712275
• Languages: English
• ISSNs: 0022-4065

Abstract

Abstract: After completing the experimental runs of a screening design, the responses under study are analyzed by statistical methods to detect the active effects. To increase the chances of correctly identifying these effects, a good analysis method should provide alternative interpretations of the data, reveal the aliasing present in the design, and search only meaningful sets of effects as defined by user-specified restrictions such as effect heredity. This article presents a mixed integer optimization strategy to analyze data from screening designs that possesses all these properties. We illustrate our method by analyzing data from real and synthetic experiments, and using simulations.