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A robust analysis of unreplicated factorials

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  • Víctor Aguirre‐Torres
  • Román de la Vara

Abstract

The existing methods for analyzing unreplicated fractional factorial experiments that do not contemplate the possibility of outliers in the data have a poor performance for detecting the active effects when that contingency becomes a reality. There are some methods to detect active effects under this experimental setup that consider outliers. We propose a new procedure based on robust regression methods to estimate the effects that allows for outliers. We perform a simulation study to compare its behavior relative to existing methods and find that the new method has a very competitive or even better power. The relative power improves as the contamination and size of outliers increase when the number of active effects is up to four. Copyright © 2012 John Wiley & Sons, Ltd.

Suggested Citation

  • Víctor Aguirre‐Torres & Román de la Vara, 2012. "A robust analysis of unreplicated factorials," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 28(3), pages 194-205, May.
    • Handle: RePEc:wly:apsmbi:v:28:y:2012:i:3:p:194-205
    DOI: 10.1002/asmb.938
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