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Low statistical power in biomedical science: a review of three human research domains
Studies with low statistical power increase the likelihood that a statistically significant finding represents a false positive result. We conducted a review of meta-analyses of studies investigating the association of biological, environmental or cognitive parameters with neurological, psychiatric...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5367316/ https://www.ncbi.nlm.nih.gov/pubmed/28386409 http://dx.doi.org/10.1098/rsos.160254 |
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author | Dumas-Mallet, Estelle Button, Katherine S. Boraud, Thomas Gonon, Francois Munafò, Marcus R. |
author_facet | Dumas-Mallet, Estelle Button, Katherine S. Boraud, Thomas Gonon, Francois Munafò, Marcus R. |
author_sort | Dumas-Mallet, Estelle |
collection | PubMed |
description | Studies with low statistical power increase the likelihood that a statistically significant finding represents a false positive result. We conducted a review of meta-analyses of studies investigating the association of biological, environmental or cognitive parameters with neurological, psychiatric and somatic diseases, excluding treatment studies, in order to estimate the average statistical power across these domains. Taking the effect size indicated by a meta-analysis as the best estimate of the likely true effect size, and assuming a threshold for declaring statistical significance of 5%, we found that approximately 50% of studies have statistical power in the 0–10% or 11–20% range, well below the minimum of 80% that is often considered conventional. Studies with low statistical power appear to be common in the biomedical sciences, at least in the specific subject areas captured by our search strategy. However, we also observe evidence that this depends in part on research methodology, with candidate gene studies showing very low average power and studies using cognitive/behavioural measures showing high average power. This warrants further investigation. |
format | Online Article Text |
id | pubmed-5367316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | The Royal Society Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-53673162017-04-06 Low statistical power in biomedical science: a review of three human research domains Dumas-Mallet, Estelle Button, Katherine S. Boraud, Thomas Gonon, Francois Munafò, Marcus R. R Soc Open Sci Psychology and Cognitive Neuroscience Studies with low statistical power increase the likelihood that a statistically significant finding represents a false positive result. We conducted a review of meta-analyses of studies investigating the association of biological, environmental or cognitive parameters with neurological, psychiatric and somatic diseases, excluding treatment studies, in order to estimate the average statistical power across these domains. Taking the effect size indicated by a meta-analysis as the best estimate of the likely true effect size, and assuming a threshold for declaring statistical significance of 5%, we found that approximately 50% of studies have statistical power in the 0–10% or 11–20% range, well below the minimum of 80% that is often considered conventional. Studies with low statistical power appear to be common in the biomedical sciences, at least in the specific subject areas captured by our search strategy. However, we also observe evidence that this depends in part on research methodology, with candidate gene studies showing very low average power and studies using cognitive/behavioural measures showing high average power. This warrants further investigation. The Royal Society Publishing 2017-02-01 /pmc/articles/PMC5367316/ /pubmed/28386409 http://dx.doi.org/10.1098/rsos.160254 Text en © 2017 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 | Psychology and Cognitive Neuroscience Dumas-Mallet, Estelle Button, Katherine S. Boraud, Thomas Gonon, Francois Munafò, Marcus R. Low statistical power in biomedical science: a review of three human research domains |
title | Low statistical power in biomedical science: a review of three human research domains |
title_full | Low statistical power in biomedical science: a review of three human research domains |
title_fullStr | Low statistical power in biomedical science: a review of three human research domains |
title_full_unstemmed | Low statistical power in biomedical science: a review of three human research domains |
title_short | Low statistical power in biomedical science: a review of three human research domains |
title_sort | low statistical power in biomedical science: a review of three human research domains |
topic | Psychology and Cognitive Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5367316/ https://www.ncbi.nlm.nih.gov/pubmed/28386409 http://dx.doi.org/10.1098/rsos.160254 |
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