A robust analysis of unreplicated factorials

Víctor Aguirre‐Torres and Román de la Vara

Applied Stochastic Models in Business and Industry, 2012, vol. 28, issue 3, 194-205

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.

Date: 2012
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https://doi.org/10.1002/asmb.938

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Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:28:y:2012:i:3:p:194-205

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