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An investigation of the false discovery rate and the misinterpretation of p-values
If you use p=0.05 to suggest that you have made a discovery, you will be wrong at least 30% of the time. If, as is often the case, experiments are underpowered, you will be wrong most of the time. This conclusion is demonstrated from several points of view. First, tree diagrams which show the close...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The Royal Society Publishing
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4448847/ https://www.ncbi.nlm.nih.gov/pubmed/26064558 http://dx.doi.org/10.1098/rsos.140216 |
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author | Colquhoun, David |
author_facet | Colquhoun, David |
author_sort | Colquhoun, David |
collection | PubMed |
description | If you use p=0.05 to suggest that you have made a discovery, you will be wrong at least 30% of the time. If, as is often the case, experiments are underpowered, you will be wrong most of the time. This conclusion is demonstrated from several points of view. First, tree diagrams which show the close analogy with the screening test problem. Similar conclusions are drawn by repeated simulations of t-tests. These mimic what is done in real life, which makes the results more persuasive. The simulation method is used also to evaluate the extent to which effect sizes are over-estimated, especially in underpowered experiments. A script is supplied to allow the reader to do simulations themselves, with numbers appropriate for their own work. It is concluded that if you wish to keep your false discovery rate below 5%, you need to use a three-sigma rule, or to insist on p≤0.001. And never use the word ‘significant’. |
format | Online Article Text |
id | pubmed-4448847 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | The Royal Society Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-44488472015-06-10 An investigation of the false discovery rate and the misinterpretation of p-values Colquhoun, David R Soc Open Sci Review Articles If you use p=0.05 to suggest that you have made a discovery, you will be wrong at least 30% of the time. If, as is often the case, experiments are underpowered, you will be wrong most of the time. This conclusion is demonstrated from several points of view. First, tree diagrams which show the close analogy with the screening test problem. Similar conclusions are drawn by repeated simulations of t-tests. These mimic what is done in real life, which makes the results more persuasive. The simulation method is used also to evaluate the extent to which effect sizes are over-estimated, especially in underpowered experiments. A script is supplied to allow the reader to do simulations themselves, with numbers appropriate for their own work. It is concluded that if you wish to keep your false discovery rate below 5%, you need to use a three-sigma rule, or to insist on p≤0.001. And never use the word ‘significant’. The Royal Society Publishing 2014-11-19 /pmc/articles/PMC4448847/ /pubmed/26064558 http://dx.doi.org/10.1098/rsos.140216 Text en © 2014 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Review Articles Colquhoun, David An investigation of the false discovery rate and the misinterpretation of p-values |
title | An investigation of the false discovery rate and the misinterpretation of p-values |
title_full | An investigation of the false discovery rate and the misinterpretation of p-values |
title_fullStr | An investigation of the false discovery rate and the misinterpretation of p-values |
title_full_unstemmed | An investigation of the false discovery rate and the misinterpretation of p-values |
title_short | An investigation of the false discovery rate and the misinterpretation of p-values |
title_sort | investigation of the false discovery rate and the misinterpretation of p-values |
topic | Review Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4448847/ https://www.ncbi.nlm.nih.gov/pubmed/26064558 http://dx.doi.org/10.1098/rsos.140216 |
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