Abstract
Factorial designs are widely used experimental plans for identifying important factors in screening studies where many factors are involved. In many practical situations where some interactions are significant, the design is supersaturated and the experimental analysis becomes infeasible due to the lack of degree of freedoms [9]. Recently, a new analysis procedure called the Stepwise Response Refinement Screener (SRRS) method is proposed to screen important effects for supersaturated designs [6]. This paper extends this method to the twolevel factorial designs. The applications to several real-life examples suggest that the SRRS method is able to retrieve similar results as the existing methods do. Simulation studies show that compared to existing methods in the literature, the SRRS method performs well in terms of the true model identification rate and the average model size.
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Phoa, F.K.H. (2013). Analysis of Factorial Designs with the Consideration of Interactions via the Stepwise Response Refinement Screener (SRRS). In: Latorre Carmona, P., Sánchez, J., Fred, A. (eds) Pattern Recognition - Applications and Methods. Advances in Intelligent Systems and Computing, vol 204. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36530-0_2
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DOI: https://doi.org/10.1007/978-3-642-36530-0_2
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