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A robust Pearson correlation test for a general point null using a surrogate bootstrap distribution
In this note we present a robust bootstrap test with good Type I error control for testing the general hypothesis H(0): ρ = ρ(0). In order to carry out this test we use what is termed a surrogate bootstrap distribution. The test was inspired by the studentized permutation for testing H(0): ρ = 0, wh...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6522008/ https://www.ncbi.nlm.nih.gov/pubmed/31095591 http://dx.doi.org/10.1371/journal.pone.0216287 |
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author | Hutson, Alan D. |
author_facet | Hutson, Alan D. |
author_sort | Hutson, Alan D. |
collection | PubMed |
description | In this note we present a robust bootstrap test with good Type I error control for testing the general hypothesis H(0): ρ = ρ(0). In order to carry out this test we use what is termed a surrogate bootstrap distribution. The test was inspired by the studentized permutation for testing H(0): ρ = 0, which was proven to be exact in certain scenarios and asymptotically correct overall. We show that the bootstrap based test is robust to a variety of distributional scenarios in terms of proper Type I error control. |
format | Online Article Text |
id | pubmed-6522008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-65220082019-05-31 A robust Pearson correlation test for a general point null using a surrogate bootstrap distribution Hutson, Alan D. PLoS One Research Article In this note we present a robust bootstrap test with good Type I error control for testing the general hypothesis H(0): ρ = ρ(0). In order to carry out this test we use what is termed a surrogate bootstrap distribution. The test was inspired by the studentized permutation for testing H(0): ρ = 0, which was proven to be exact in certain scenarios and asymptotically correct overall. We show that the bootstrap based test is robust to a variety of distributional scenarios in terms of proper Type I error control. Public Library of Science 2019-05-16 /pmc/articles/PMC6522008/ /pubmed/31095591 http://dx.doi.org/10.1371/journal.pone.0216287 Text en © 2019 Alan D. Hutson http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hutson, Alan D. A robust Pearson correlation test for a general point null using a surrogate bootstrap distribution |
title | A robust Pearson correlation test for a general point null using a surrogate bootstrap distribution |
title_full | A robust Pearson correlation test for a general point null using a surrogate bootstrap distribution |
title_fullStr | A robust Pearson correlation test for a general point null using a surrogate bootstrap distribution |
title_full_unstemmed | A robust Pearson correlation test for a general point null using a surrogate bootstrap distribution |
title_short | A robust Pearson correlation test for a general point null using a surrogate bootstrap distribution |
title_sort | robust pearson correlation test for a general point null using a surrogate bootstrap distribution |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6522008/ https://www.ncbi.nlm.nih.gov/pubmed/31095591 http://dx.doi.org/10.1371/journal.pone.0216287 |
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