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The factor aliased effect number pattern and its application in experimental planning
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Journal Article
The factor aliased effect number pattern and its application in experimental planning
2013
Overview
Optimality criteria are usually used to choose fractional factorial designs in applications. Within an optimal design, the effects of factors assigned to different columns may be estimated with different precisions. Among factors to be investigated in an experiment, the user often has prior information on their relative importance. Thus, it is beneficial to assign most important factors to columns enabling most precise estimation. In this paper, we introduce a criterion to rank the columns of a regular design and use the criterion to GMC designs accordingly. We study the mathematical properties of the new ranking practice and provide concrete guidance on assigning factors in some GMC designs. Les critères d'optimalité sont généralement utilisés pour choisir les plans factoriels fractionnaires dans le cadre d'applications. Au sein d'un plan optimal, les effets des facteurs attribués à différentes colonnes peuvent être évalués à divers degrés de précision. Souvent, de l'information est disponible sur les facteurs à examiner au cours d'une expérience et sur leur importance relative. Il est alors pertinent d'assigner les facteurs les plus importants aux colonnes offrant l'estimation la plus précise. Dans cet article, les auteurs présentent un critère permettant de classer les colonnes d'un plan classique et l'utilisent dans le cadre de plans généraux minimisant les effets confondants d'ordre inférieur (GMC). Ils étudient les propriétés mathématiques de la nouvelle méthode de classement et proposent des directives concrètes à propos de l'assignation des facteurs dans certains plans GMC.
Publisher
Blackwell Publishing Ltd,Statistical Society of Canada,Wiley Subscription Services, Inc
Subject
