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Results for Two-Level Designs with General Minimum Lower-Order Confounding

The general minimum lower-order confounding (GMC) criterion for two-level design not only reveals the confounding information of factor effects but also provides a good way to select the optimal design, which was proposed by Zhang et al. (2008). The criterion is based on the aliased effect-number pa...

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Detalles Bibliográficos
Autores principales: Li, Zhi Ming, Zhang, Run Chu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4488011/
https://www.ncbi.nlm.nih.gov/pubmed/26167520
http://dx.doi.org/10.1155/2015/163234
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author Li, Zhi Ming
Zhang, Run Chu
author_facet Li, Zhi Ming
Zhang, Run Chu
author_sort Li, Zhi Ming
collection PubMed
description The general minimum lower-order confounding (GMC) criterion for two-level design not only reveals the confounding information of factor effects but also provides a good way to select the optimal design, which was proposed by Zhang et al. (2008). The criterion is based on the aliased effect-number pattern (AENP). Therefore, it is very important to study properties of AENP for two-level GMC design. According to the ordering of elements in the AENP, the confounding information between lower-order factor effects is more important than that of higher-order effects. For two-level GMC design, this paper mainly shows the interior principles to calculate the leading elements (1) (#) C (2) and (2) (#) C (2) in the AENP. Further, their mathematical formulations are obtained for every GMC 2(n−m) design with N = 2(n−m) according to two cases: (i) 5N/16 + 1 ≤ n < N/2 and (ii) N/2 ≤ n ≤ N − 1.
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spelling pubmed-44880112015-07-12 Results for Two-Level Designs with General Minimum Lower-Order Confounding Li, Zhi Ming Zhang, Run Chu ScientificWorldJournal Research Article The general minimum lower-order confounding (GMC) criterion for two-level design not only reveals the confounding information of factor effects but also provides a good way to select the optimal design, which was proposed by Zhang et al. (2008). The criterion is based on the aliased effect-number pattern (AENP). Therefore, it is very important to study properties of AENP for two-level GMC design. According to the ordering of elements in the AENP, the confounding information between lower-order factor effects is more important than that of higher-order effects. For two-level GMC design, this paper mainly shows the interior principles to calculate the leading elements (1) (#) C (2) and (2) (#) C (2) in the AENP. Further, their mathematical formulations are obtained for every GMC 2(n−m) design with N = 2(n−m) according to two cases: (i) 5N/16 + 1 ≤ n < N/2 and (ii) N/2 ≤ n ≤ N − 1. Hindawi Publishing Corporation 2015 2015-06-16 /pmc/articles/PMC4488011/ /pubmed/26167520 http://dx.doi.org/10.1155/2015/163234 Text en Copyright © 2015 Z. M. Li and R. C. Zhang. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Li, Zhi Ming
Zhang, Run Chu
Results for Two-Level Designs with General Minimum Lower-Order Confounding
title Results for Two-Level Designs with General Minimum Lower-Order Confounding
title_full Results for Two-Level Designs with General Minimum Lower-Order Confounding
title_fullStr Results for Two-Level Designs with General Minimum Lower-Order Confounding
title_full_unstemmed Results for Two-Level Designs with General Minimum Lower-Order Confounding
title_short Results for Two-Level Designs with General Minimum Lower-Order Confounding
title_sort results for two-level designs with general minimum lower-order confounding
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4488011/
https://www.ncbi.nlm.nih.gov/pubmed/26167520
http://dx.doi.org/10.1155/2015/163234
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