A mixed integer optimization approach for model selection in screening experiments
- Journal of Quality Technology
- July 2021
- Volume 53 Issue 3
- pp. 243-266
- Vazquez, Alan R., Schoen, Eric D., Goos, Peter
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.*Supplemental material accessed online through Taylor & Francis.