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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...

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Detalles Bibliográficos
Autores principales: Dumas-Mallet, Estelle, Button, Katherine S., Boraud, Thomas, Gonon, Francois, Munafò, Marcus R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2017
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.
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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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