Institute of Mathematical Statistics Lecture Notes - Monograph Series

Statistical modeling for experiments with sliding levels

Shao-Wei Cheng, C. F. J. Wu, and Longcheen Huwang

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Design of experiment with related factors can be implemented by using the technique of sliding levels. Taguchi (1987) proposed an analysis strategy by re-centering and re-scaling the slid factors. Hamada and Wu (1995) showed via counter examples that in many cases the interactions cannot be completely eliminated by Taguchi’s strategy. They proposed an alternative method in which the slid factors are modeled by nested effects. In this work we show the inadequacy of both methods when the objective is response prediction. We propose an analysis method based on a response surface model, and demonstrate its superiority for prediction. We also study the relationships between these three modeling strategies.

Chapter information

Hwai-Chung Ho, Ching-Kang Ing, Tze Leung Lai, eds., Time Series and Related Topics: In Memory of Ching-Zong Wei (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2006), 245-256

First available in Project Euclid: 28 November 2007

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Digital Object Identifier

Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 62K15: Factorial designs 62K20: Response surface designs
Secondary: 62P30: Applications in engineering and industry

irregular experimental region nested effect re-centering and re-scaling response prediction response surface modeling robust parameter design

Copyright © 2006, Institute of Mathematical Statistics


Cheng, Shao-Wei; Wu, C. F. J.; Huwang, Longcheen. Statistical modeling for experiments with sliding levels. Time Series and Related Topics, 245--256, Institute of Mathematical Statistics, Beachwood, Ohio, USA, 2006. doi:10.1214/074921706000001085.

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