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Recommendations in pre-registrations and internal review board proposals promote formal power analyses but do not increase sample size

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Listed:
  • Marjan Bakker
  • Coosje L S Veldkamp
  • Olmo R van den Akker
  • Marcel A L M van Assen
  • Elise Crompvoets
  • How Hwee Ong
  • Jelte M Wicherts

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.

Suggested Citation

  • Marjan Bakker & Coosje L S Veldkamp & Olmo R van den Akker & Marcel A L M van Assen & Elise Crompvoets & How Hwee Ong & Jelte M Wicherts, 2020. "Recommendations in pre-registrations and internal review board proposals promote formal power analyses but do not increase sample size," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-15, July.
    • Handle: RePEc:plo:pone00:0236079
    DOI: 10.1371/journal.pone.0236079
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    References listed on IDEAS

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    1. Daniele Fanelli, 2010. "“Positive” Results Increase Down the Hierarchy of the Sciences," PLOS ONE, Public Library of Science, vol. 5(4), pages 1-10, April.
    2. Colin F. Camerer & Anna Dreber & Felix Holzmeister & Teck-Hua Ho & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Gideon Nave & Brian A. Nosek & Thomas Pfeiffer & Adam Altmejd & Nick Buttrick , 2018. "Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015," Nature Human Behaviour, Nature, vol. 2(9), pages 637-644, September.
    3. Nosek, Brian A. & Ebersole, Charles R. & DeHaven, Alexander Carl & Mellor, David Thomas, 2018. "The Preregistration Revolution," OSF Preprints 2dxu5, Center for Open Science.
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    1. Giorgi, Francesca, 2021. "A new method to explore inferential risks associated with each study in a meta-analysis: An approach based on Design Analysis," Thesis Commons n5y8b, Center for Open Science.

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