Loading…

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...

Full description

Saved in:
Bibliographic Details
Published in:Royal Society open science 2017-02, Vol.4 (2), p.160254-160254
Main Authors: Dumas-Mallet, Estelle, Button, Katherine S., Boraud, Thomas, Gonon, Francois, Munafò, Marcus R.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c680t-b84c4130782cb4c7fd2782827bbb2de4a47176647f426fc4cd773170e71f79d13
cites cdi_FETCH-LOGICAL-c680t-b84c4130782cb4c7fd2782827bbb2de4a47176647f426fc4cd773170e71f79d13
container_end_page 160254
container_issue 2
container_start_page 160254
container_title Royal Society open science
container_volume 4
creator Dumas-Mallet, Estelle
Button, Katherine S.
Boraud, Thomas
Gonon, Francois
Munafò, Marcus R.
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.
doi_str_mv 10.1098/rsos.160254
format article
fullrecord <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_984080f957b7424188cbaad890b3300f</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_984080f957b7424188cbaad890b3300f</doaj_id><sourcerecordid>1885953627</sourcerecordid><originalsourceid>FETCH-LOGICAL-c680t-b84c4130782cb4c7fd2782827bbb2de4a47176647f426fc4cd773170e71f79d13</originalsourceid><addsrcrecordid>eNp9kU1v1DAQhiMEolXpiTvyEQltGX87HJBQxUellSpReuJg2Y7T9SqJFzvZ1fLrcZtS7R7g5PHM62dm_FbVawwXGGr1PuWYL7AAwtmz6pQAZwsugT4_iE-q85zXAIA5UCnky-qEKKoEg_q0ul3GHcqjGUMegzMd2sSdTygMyIbY--Yhl13wg_MfkEHJb4PfodiicZW8R6upN0PJZm-SW6Em9iYM-VX1ojVd9ueP51l1--Xzj8tvi-X116vLT8uFEwrGhVXMMUxBKuIsc7JtSAkVkdZa0nhmmMRSCCZbRkTrmGukpFiCl7iVdYPpWXU1c5to1nqTQm_SXkcT9EMipjttUtmr87pWDBS0NZdWMsKwUs4a06gaLKUAbWF9nFmbyZbFnR_GZLoj6HFlCCt9F7eaU1GmEgXw9hGQ4q_J51H3ITvfdWbwccq6tOR1ERNZpO9mqUsx5-TbpzYY9L2v-t5XPfta1G8OJ3vS_nWxCGAWpLgv3x2LXeNer-OUhnL9B_Pn_558v7m-2bJANCiKQdCac_07bGYE0yHnyWtySDyi_wE1is5g</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1885953627</pqid></control><display><type>article</type><title>Low statistical power in biomedical science: a review of three human research domains</title><source>Open Access: PubMed Central</source><source>Royal Society Open Access</source><creator>Dumas-Mallet, Estelle ; Button, Katherine S. ; Boraud, Thomas ; Gonon, Francois ; Munafò, Marcus R.</creator><creatorcontrib>Dumas-Mallet, Estelle ; Button, Katherine S. ; Boraud, Thomas ; Gonon, Francois ; Munafò, Marcus R.</creatorcontrib><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.</description><identifier>ISSN: 2054-5703</identifier><identifier>EISSN: 2054-5703</identifier><identifier>DOI: 10.1098/rsos.160254</identifier><identifier>PMID: 28386409</identifier><language>eng</language><publisher>England: The Royal Society Publishing</publisher><subject>Neurology ; Psychiatry ; Psychology And Cognitive Neuroscience ; Reproducibility ; Somatic Disease ; Statistical Power</subject><ispartof>Royal Society open science, 2017-02, Vol.4 (2), p.160254-160254</ispartof><rights>2017 The Authors.</rights><rights>2017 The Authors. 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c680t-b84c4130782cb4c7fd2782827bbb2de4a47176647f426fc4cd773170e71f79d13</citedby><cites>FETCH-LOGICAL-c680t-b84c4130782cb4c7fd2782827bbb2de4a47176647f426fc4cd773170e71f79d13</cites><orcidid>0000-0002-4049-993X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5367316/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5367316/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,3322,27147,27924,27925,53791,53793,55555,55565</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28386409$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Dumas-Mallet, Estelle</creatorcontrib><creatorcontrib>Button, Katherine S.</creatorcontrib><creatorcontrib>Boraud, Thomas</creatorcontrib><creatorcontrib>Gonon, Francois</creatorcontrib><creatorcontrib>Munafò, Marcus R.</creatorcontrib><title>Low statistical power in biomedical science: a review of three human research domains</title><title>Royal Society open science</title><addtitle>R. Soc. open sci</addtitle><addtitle>R Soc Open Sci</addtitle><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.</description><subject>Neurology</subject><subject>Psychiatry</subject><subject>Psychology And Cognitive Neuroscience</subject><subject>Reproducibility</subject><subject>Somatic Disease</subject><subject>Statistical Power</subject><issn>2054-5703</issn><issn>2054-5703</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp9kU1v1DAQhiMEolXpiTvyEQltGX87HJBQxUellSpReuJg2Y7T9SqJFzvZ1fLrcZtS7R7g5PHM62dm_FbVawwXGGr1PuWYL7AAwtmz6pQAZwsugT4_iE-q85zXAIA5UCnky-qEKKoEg_q0ul3GHcqjGUMegzMd2sSdTygMyIbY--Yhl13wg_MfkEHJb4PfodiicZW8R6upN0PJZm-SW6Em9iYM-VX1ojVd9ueP51l1--Xzj8tvi-X116vLT8uFEwrGhVXMMUxBKuIsc7JtSAkVkdZa0nhmmMRSCCZbRkTrmGukpFiCl7iVdYPpWXU1c5to1nqTQm_SXkcT9EMipjttUtmr87pWDBS0NZdWMsKwUs4a06gaLKUAbWF9nFmbyZbFnR_GZLoj6HFlCCt9F7eaU1GmEgXw9hGQ4q_J51H3ITvfdWbwccq6tOR1ERNZpO9mqUsx5-TbpzYY9L2v-t5XPfta1G8OJ3vS_nWxCGAWpLgv3x2LXeNer-OUhnL9B_Pn_558v7m-2bJANCiKQdCac_07bGYE0yHnyWtySDyi_wE1is5g</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>Dumas-Mallet, Estelle</creator><creator>Button, Katherine S.</creator><creator>Boraud, Thomas</creator><creator>Gonon, Francois</creator><creator>Munafò, Marcus R.</creator><general>The Royal Society Publishing</general><general>The Royal Society</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-4049-993X</orcidid></search><sort><creationdate>20170201</creationdate><title>Low statistical power in biomedical science: a review of three human research domains</title><author>Dumas-Mallet, Estelle ; Button, Katherine S. ; Boraud, Thomas ; Gonon, Francois ; Munafò, Marcus R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c680t-b84c4130782cb4c7fd2782827bbb2de4a47176647f426fc4cd773170e71f79d13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Neurology</topic><topic>Psychiatry</topic><topic>Psychology And Cognitive Neuroscience</topic><topic>Reproducibility</topic><topic>Somatic Disease</topic><topic>Statistical Power</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dumas-Mallet, Estelle</creatorcontrib><creatorcontrib>Button, Katherine S.</creatorcontrib><creatorcontrib>Boraud, Thomas</creatorcontrib><creatorcontrib>Gonon, Francois</creatorcontrib><creatorcontrib>Munafò, Marcus R.</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Royal Society open science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dumas-Mallet, Estelle</au><au>Button, Katherine S.</au><au>Boraud, Thomas</au><au>Gonon, Francois</au><au>Munafò, Marcus R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Low statistical power in biomedical science: a review of three human research domains</atitle><jtitle>Royal Society open science</jtitle><stitle>R. Soc. open sci</stitle><addtitle>R Soc Open Sci</addtitle><date>2017-02-01</date><risdate>2017</risdate><volume>4</volume><issue>2</issue><spage>160254</spage><epage>160254</epage><pages>160254-160254</pages><issn>2054-5703</issn><eissn>2054-5703</eissn><abstract>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.</abstract><cop>England</cop><pub>The Royal Society Publishing</pub><pmid>28386409</pmid><doi>10.1098/rsos.160254</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-4049-993X</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2054-5703
ispartof Royal Society open science, 2017-02, Vol.4 (2), p.160254-160254
issn 2054-5703
2054-5703
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_984080f957b7424188cbaad890b3300f
source Open Access: PubMed Central; Royal Society Open Access
subjects Neurology
Psychiatry
Psychology And Cognitive Neuroscience
Reproducibility
Somatic Disease
Statistical Power
title Low statistical power in biomedical science: a review of three human research domains
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T21%3A02%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Low%20statistical%20power%20in%20biomedical%20science:%20a%20review%20of%20three%20human%20research%20domains&rft.jtitle=Royal%20Society%20open%20science&rft.au=Dumas-Mallet,%20Estelle&rft.date=2017-02-01&rft.volume=4&rft.issue=2&rft.spage=160254&rft.epage=160254&rft.pages=160254-160254&rft.issn=2054-5703&rft.eissn=2054-5703&rft_id=info:doi/10.1098/rsos.160254&rft_dat=%3Cproquest_doaj_%3E1885953627%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c680t-b84c4130782cb4c7fd2782827bbb2de4a47176647f426fc4cd773170e71f79d13%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1885953627&rft_id=info:pmid/28386409&rfr_iscdi=true