Blocked factor aliased effect-number pattern and column rank of blocked regular designs

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• 作者：Dongying Wang ; Shili Ye ; Qi Zhou ; Runchu Zhang
• 关键词：Aliased effect ; number pattern ; Blocked ; Factor aliased effect ; number pattern ; Fractional factorial design ; General minimum lower order confounding (GMC)
• 刊名：Metrika
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：80
• 期：2
• 页码：133-152
• 全文大小：
• 刊物类别：Mathematics and Statistics
• 刊物主题：Statistics, general; Statistics for Business/Economics/Mathematical Finance/Insurance; Probability Theory and Stochastic Processes; Economic Theory/Quantitative Economics/Mathematical Methods;
• 出版者：Springer Berlin Heidelberg
• ISSN：1435-926X
• 卷排序：80

文摘

In factorial experiments, estimation precision of specific factor effects depends not only on design selection but also on factor assignments to columns of selected designs. Usually, different columns in a design play different roles when estimating factor effects. Zhou et al. (Can J Stat 41:540-555, 2013) introduced a factor aliased effect-number pattern (F-AENP) and proposed a column ranking scheme for all the GMC \(2^{n-m}\) designs with \(5N/16+1\le n\le N-1\), where \(N=2^{n-m}\). In this paper, we first introduce a blocked factor aliased effect-number pattern (B-F-AENP) for blocked regular designs as an extension of the F-AENP. Then, by using the B-F-AENP, we propose a column ranking scheme for all the B\(^1\)-GMC \(2^{n-m}:2^s\) designs with \(5N/16+1\le n\le N-1\), as well as an assignment strategy for important factors.