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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
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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. |
format | Online Article Text |
id | pubmed-4488011 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
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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