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...
Saved in:
Published in: | Royal Society open science 2017-02, Vol.4 (2), p.160254-160254 |
---|---|
Main Authors: | , , , , |
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 |