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A New Powerful Nonparametric Rank Test for Ordered Alternative Problem
We propose a new nonparametric test for ordered alternative problem based on the rank difference between two observations from different groups. These groups are assumed to be independent from each other. The exact mean and variance of the test statistic under the null distribution are derived, and...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236087/ https://www.ncbi.nlm.nih.gov/pubmed/25405757 http://dx.doi.org/10.1371/journal.pone.0112924 |
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author | Shan, Guogen Young, Daniel Kang, Le |
author_facet | Shan, Guogen Young, Daniel Kang, Le |
author_sort | Shan, Guogen |
collection | PubMed |
description | We propose a new nonparametric test for ordered alternative problem based on the rank difference between two observations from different groups. These groups are assumed to be independent from each other. The exact mean and variance of the test statistic under the null distribution are derived, and its asymptotic distribution is proven to be normal. Furthermore, an extensive power comparison between the new test and other commonly used tests shows that the new test is generally more powerful than others under various conditions, including the same type of distribution, and mixed distributions. A real example from an anti-hypertensive drug trial is provided to illustrate the application of the tests. The new test is therefore recommended for use in practice due to easy calculation and substantial power gain. |
format | Online Article Text |
id | pubmed-4236087 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-42360872014-11-21 A New Powerful Nonparametric Rank Test for Ordered Alternative Problem Shan, Guogen Young, Daniel Kang, Le PLoS One Research Article We propose a new nonparametric test for ordered alternative problem based on the rank difference between two observations from different groups. These groups are assumed to be independent from each other. The exact mean and variance of the test statistic under the null distribution are derived, and its asymptotic distribution is proven to be normal. Furthermore, an extensive power comparison between the new test and other commonly used tests shows that the new test is generally more powerful than others under various conditions, including the same type of distribution, and mixed distributions. A real example from an anti-hypertensive drug trial is provided to illustrate the application of the tests. The new test is therefore recommended for use in practice due to easy calculation and substantial power gain. Public Library of Science 2014-11-18 /pmc/articles/PMC4236087/ /pubmed/25405757 http://dx.doi.org/10.1371/journal.pone.0112924 Text en © 2014 Shan et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Shan, Guogen Young, Daniel Kang, Le A New Powerful Nonparametric Rank Test for Ordered Alternative Problem |
title | A New Powerful Nonparametric Rank Test for Ordered Alternative Problem |
title_full | A New Powerful Nonparametric Rank Test for Ordered Alternative Problem |
title_fullStr | A New Powerful Nonparametric Rank Test for Ordered Alternative Problem |
title_full_unstemmed | A New Powerful Nonparametric Rank Test for Ordered Alternative Problem |
title_short | A New Powerful Nonparametric Rank Test for Ordered Alternative Problem |
title_sort | new powerful nonparametric rank test for ordered alternative problem |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236087/ https://www.ncbi.nlm.nih.gov/pubmed/25405757 http://dx.doi.org/10.1371/journal.pone.0112924 |
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