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Faculty, if you know of tenure-track positions that we should be listing, or see an error, please e-mail us at chemjobber@gmail.com

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how researchers use (and misuse) G*power
Important preprint by Thibault et al
medrxiv.org/content/10.1101/20

An evaluation of reproducibility and errors in published sample size calculations performed using G*Power

Background. Published studies in the life and health sciences often employ sample sizes that are too small to detect realistic effect sizes. This shortcoming increases the rate of false positives and false negatives, giving rise to a potentially misleading scientific record. To address this shortcoming, many researchers now use point-and-click software to run sample size calculations. Objective. We aimed to (1) estimate how many published articles report using the G*Power sample size calculation software; (2) assess whether these calculations are reproducible and (3) error-free; and (4) assess how often these calculations use G*Power's default option for mixed-design ANOVAs; which can be misleading and output sample sizes that are too small for a researcher's intended purpose. Method. We randomly sampled open access articles from PubMed Central published between 2017 and 2022 and used a coding form to manually assess 95 sample size calculations for reproducibility and errors. Results. We estimate that more than 48,000 articles published between 2017 and 2022 and indexed in PubMed Central or PubMed report using G*Power (i.e., 0.65% [95% CI: 0.62% - 0.67%] of articles). We could reproduce 2% (2/95) of the sample size calculations without making any assumptions, and likely reproduce another 28% (27/95) after making assumptions. Many calculations were not reported transparently enough to assess whether an error was present (75%; 71/95) or whether the sample size calculation was for a statistical test that appeared in the results section of the publication (48%; 46/95). Few articles that performed a calculation for a mixed-design ANOVA unambiguously selected the non-default option (8%; 3/36). Conclusion. Published sample size calculations that use G*Power are not transparently reported and may not be well-informed. Given the popularity of software packages like G*Power, they present an intervention point to increase the prevalence of informative sample size calculations. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Protocols <https://doi.org/10.17605/OSF.IO/UJXHW> ### Funding Statement Robert Thibault was supported by a general support grant awarded to METRICS from Arnold Ventures and a postdoctoral fellowship from the Canadian Institutes of Health Research. Robert Thibault will serve as guarantor for the contents of this paper. Hugo Pedder was supported by the UK National Institute for Health and Social Care Excellence (NICE) via the Bristol Technology Assessment Group and the NICE Technical Support Unit. The funders had no role in the preparation of this manuscript or the decision to publish. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data, data dictionaries, analysis scripts, and other materials related to this study are publicly available at https://osf.io/msz24/. The study protocol was registered on 31 May 2022 at https://doi.org/10.17605/OSF.IO/UJXHW. Discrepancies between this manuscript and the registered protocol are outlined in Supplementary Material A. The analysis script can be rerun by selecting "Reproducible Run" in the Code Ocean container available at https://doi.org/10.24433/CO.4349082.v1. <https://osf.io/msz24/> <https://doi.org/10.24433/CO.4349082.v1>

www.medrxiv.org
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Long COVID can change your life--even if you've seemingly recovered. “People who have recovered from long COVID can suffer relapses or flare-ups from new viral infections — not just from COVID but from cold, flu, and other viral pathogens, researchers have found.”

The ONLY way to prevent Long COVID is to avoid your next infection with #COVID19.

medscape.com/viewarticle/cold-

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Barcelona has banned Airbnb.

"The decision is designed to solve what Collboni described as "Barcelona's biggest problem" – the housing crisis that has seen residents and workers priced out of the market – by returning the 10,000 apartments currently listed as short-term rentals on Airbnb and other platforms into the housing market. "

bbc.com/travel/article/2024070

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#Neuralink competitor #Paradromics gears up to test its brain implant on humans cnbc.com/2024/06/21/paradromic "Paradromics, which was founded in 2015, anticipates the devices will retail for about $100,000 each"; #BCI #NeuroTech

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One particularly cool discovery from the new Harvard-Google brain images:

Some brain cells are arranged in mirror-image pairs, for reasons not yet well understood.

science.org/doi/10.1126/scienc #science #brain #mind #neuroscience #tech

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Allen’s hummingbird cruising through the Mexican bush sage

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Post doc position available in my group, would be great if you could boost; if you are a theoretical / computational population genomicist looking for a post doc, please get in touch!

bit.ly/3QIfeda

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Because there are never enough Green Herons on Mastodon, here's one.

#birds

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▓▓▓▓▓░░░░░░░░░░ 36%

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"Researchers publish largest-ever dataset of neural connections

A cubic millimeter of brain tissue may not sound like much. But considering that that tiny square contains 57,000 cells, 230 millimeters of blood vessels, and 150 million synapses, all amounting to 1,400 terabytes of data, Harvard and Google researchers have just accomplished something stupendous."

news.harvard.edu/gazette/story

@science

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Truly amazing: This 1 cubic mm of human brain tissue, about a millionth of a whole brain, has ~150 million synapses and results in 1.4 petabytes of data! Wonderful renderings in the article, too. #neuroscience

popsci.com/science/see-the-mos

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