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

2024-07-16 health systems and quality improvement Title + abstract only
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BackgroundPublished 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. ObjectiveWe aimed to (1) estimate how many published articles report using the G*Power sample size calculation so...

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