Powerful Foldover Designs
Jonathan W. Stallrich, Rakhi Singh, Kyle Vogt-Lowell, Fanxing Li

TL;DR
This paper enhances foldover screening designs by introducing a new construction algorithm that improves variance estimation and model selection, especially when effect sparsity and hierarchy assumptions are violated.
Contribution
It presents a novel design construction method that maximizes screening power and an augmented analysis approach to improve variance estimation and model selection.
Findings
Designs outperform traditional methods when effect principles do not hold.
New algorithms optimize confidence interval criteria for better screening.
Simulation and real data demonstrate improved performance.
Abstract
The foldover technique for screening designs is well known to guarantee zero aliasing of the main effect estimators with respect to two factor interactions and quadratic effects. It is a key feature of many popular response surface designs, including central composite designs, definitive screening designs, and most orthogonal, minimally-aliased response surface designs. In this paper, we show the foldover technique is even more powerful, because it produces degrees of freedom for a variance estimator that is independent of model selection. These degrees of freedom are characterized as either pure error or fake factor degrees of freedom. A fast design construction algorithm is presented that minimizes the expected confidence interval criterion to maximize the power of screening main effects. An augmented design and analysis method is also presented to avoid having too many degrees of…
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