Open AccessRecommendations in pre-registrations and internal review board proposals promote formal power analyses but do not increase sample size
Author(s) -
Marjan Bakker,
Coosje Lisabet Sterre Veldkamp,
Olmo R. van den Akker,
Marcel A.L.M. van Assen,
Elise Anne Victoire Crompvoets,
How Hwee Ong,
Jelte M. Wicherts
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0236079
Subject(s) - sample size determination , sample (material) , statistical power , power (physics) , statistics , computer science , psychology , medical education , medicine , mathematics , chemistry , physics , chromatography , quantum mechanics
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.