Recommendations in pre-registrations and internal review board proposals promote formal power analyses but do not increase sample size
In this preregistered study, we investigated whether the statistical power of a study is higher when researchers are asked to make a formal power analysis before collecting data. We compared the sample size descriptions from two sources: (i) a sample of pre-registrations created according to the gui...
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| Veröffentlicht in: | PloS one 2020-07, Vol.15 (7), p.e0236079-e0236079 |
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| creator | Bakker, Marjan Veldkamp, Coosje L S van den Akker, Olmo R van Assen, Marcel A L M Crompvoets, Elise Ong, How Hwee Wicherts, Jelte M |
| description | In this preregistered study, we investigated whether the statistical power of a study is higher when researchers are asked to make a formal power analysis before collecting data. We compared the sample size descriptions from two sources: (i) a sample of pre-registrations created according to the guidelines for the Center for Open Science Preregistration Challenge (PCRs) and a sample of institutional review board (IRB) proposals from Tilburg School of Behavior and Social Sciences, which both include a recommendation to do a formal power analysis, and (ii) a sample of pre-registrations created according to the guidelines for Open Science Framework Standard Pre-Data Collection Registrations (SPRs) in which no guidance on sample size planning is given. We found that PCRs and IRBs (72%) more often included sample size decisions based on power analyses than the SPRs (45%). However, this did not result in larger planned sample sizes. The determined sample size of the PCRs and IRB proposals (Md = 90.50) was not higher than the determined sample size of the SPRs (Md = 126.00; W = 3389.5, p = 0.936). Typically, power analyses in the registrations were conducted with G*power, assuming a medium effect size, α = .05 and a power of .80. Only 20% of the power analyses contained enough information to fully reproduce the results and only 62% of these power analyses pertained to the main hypothesis test in the pre-registration. Therefore, we see ample room for improvements in the quality of the registrations and we offer several recommendations to do so. |
| doi_str_mv | 10.1371/journal.pone.0236079 |
| format | Article |
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We compared the sample size descriptions from two sources: (i) a sample of pre-registrations created according to the guidelines for the Center for Open Science Preregistration Challenge (PCRs) and a sample of institutional review board (IRB) proposals from Tilburg School of Behavior and Social Sciences, which both include a recommendation to do a formal power analysis, and (ii) a sample of pre-registrations created according to the guidelines for Open Science Framework Standard Pre-Data Collection Registrations (SPRs) in which no guidance on sample size planning is given. We found that PCRs and IRBs (72%) more often included sample size decisions based on power analyses than the SPRs (45%). However, this did not result in larger planned sample sizes. The determined sample size of the PCRs and IRB proposals (Md = 90.50) was not higher than the determined sample size of the SPRs (Md = 126.00; W = 3389.5, p = 0.936). Typically, power analyses in the registrations were conducted with G*power, assuming a medium effect size, α = .05 and a power of .80. Only 20% of the power analyses contained enough information to fully reproduce the results and only 62% of these power analyses pertained to the main hypothesis test in the pre-registration. Therefore, we see ample room for improvements in the quality of the registrations and we offer several recommendations to do so.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0236079</identifier><identifier>PMID: 32735597</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Biology and Life Sciences ; Comparative analysis ; Computer and Information Sciences ; Data collection ; Decision analysis ; Engineering and Technology ; Ethics Committees, Research ; Evaluation ; Guidelines ; Hypotheses ; Medical ethics ; Physical Sciences ; Proposals ; Psychology ; Registration ; Research and Analysis Methods ; Research ethics ; Researchers ; Sample Size ; Science Policy ; Social behavior ; Social Sciences ; Statistical methods ; Statistics as Topic - methods ; Studies ; Test reliability</subject><ispartof>PloS one, 2020-07, Vol.15 (7), p.e0236079-e0236079</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Bakker et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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We compared the sample size descriptions from two sources: (i) a sample of pre-registrations created according to the guidelines for the Center for Open Science Preregistration Challenge (PCRs) and a sample of institutional review board (IRB) proposals from Tilburg School of Behavior and Social Sciences, which both include a recommendation to do a formal power analysis, and (ii) a sample of pre-registrations created according to the guidelines for Open Science Framework Standard Pre-Data Collection Registrations (SPRs) in which no guidance on sample size planning is given. We found that PCRs and IRBs (72%) more often included sample size decisions based on power analyses than the SPRs (45%). However, this did not result in larger planned sample sizes. The determined sample size of the PCRs and IRB proposals (Md = 90.50) was not higher than the determined sample size of the SPRs (Md = 126.00; W = 3389.5, p = 0.936). 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internal review board proposals promote formal power analyses but do not increase sample size</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2020-07-31</date><risdate>2020</risdate><volume>15</volume><issue>7</issue><spage>e0236079</spage><epage>e0236079</epage><pages>e0236079-e0236079</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>In this preregistered study, we investigated whether the statistical power of a study is higher when researchers are asked to make a formal power analysis before collecting data. We compared the sample size descriptions from two sources: (i) a sample of pre-registrations created according to the guidelines for the Center for Open Science Preregistration Challenge (PCRs) and a sample of institutional review board (IRB) proposals from Tilburg School of Behavior and Social Sciences, which both include a recommendation to do a formal power analysis, and (ii) a sample of pre-registrations created according to the guidelines for Open Science Framework Standard Pre-Data Collection Registrations (SPRs) in which no guidance on sample size planning is given. We found that PCRs and IRBs (72%) more often included sample size decisions based on power analyses than the SPRs (45%). However, this did not result in larger planned sample sizes. The determined sample size of the PCRs and IRB proposals (Md = 90.50) was not higher than the determined sample size of the SPRs (Md = 126.00; W = 3389.5, p = 0.936). Typically, power analyses in the registrations were conducted with G*power, assuming a medium effect size, α = .05 and a power of .80. Only 20% of the power analyses contained enough information to fully reproduce the results and only 62% of these power analyses pertained to the main hypothesis test in the pre-registration. Therefore, we see ample room for improvements in the quality of the registrations and we offer several recommendations to do so.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>32735597</pmid><doi>10.1371/journal.pone.0236079</doi><tpages>e0236079</tpages><orcidid>https://orcid.org/0000-0001-9024-337X</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Biology and Life Sciences Comparative analysis Computer and Information Sciences Data collection Decision analysis Engineering and Technology Ethics Committees, Research Evaluation Guidelines Hypotheses Medical ethics Physical Sciences Proposals Psychology Registration Research and Analysis Methods Research ethics Researchers Sample Size Science Policy Social behavior Social Sciences Statistical methods Statistics as Topic - methods Studies Test reliability |
| title | Recommendations in pre-registrations and internal review board proposals promote formal power analyses but do not increase sample size |
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