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Caring about Power Analyses.

Jennifer E Murray1, Scott T Barrett1, Rebecca L Brock1

  • 1Department of Psychology, University of Nebraska-Lincoln , Lincoln, Nebraska 68588-0308, United States.

ACS Chemical Neuroscience
|September 22, 2017
PubMed
Summary
This summary is machine-generated.

Statistical power and effect size are crucial for reducing wasted research. This viewpoint offers guidance on power analyses and reporting statistics to improve experimental design and reproducibility.

Keywords:
Data analyseseffect sizereplication crisisscientific rigor

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Area of Science:

  • Biomedical research methodology
  • Scientific reproducibility

Background:

  • Significant research waste (50-85%) stems from nonreproducible and exaggerated findings.
  • National Institutes of Health mandates emphasize scientific rigor and considering sex as a biological variable.

Purpose of the Study:

  • Provide recommendations and resources for power analyses to enhance experimental rigor.
  • Offer guidance on reporting key statistics to aid in sample size estimation for future research.

Main Methods:

  • The viewpoint discusses principles of statistical power and effect size in experimental design.
  • It suggests best practices for reporting statistical information in publications.

Main Results:

  • Implementing robust power analyses can decrease research waste.
  • Clear reporting of statistical methods enhances the ability of other researchers to replicate and build upon findings.

Conclusions:

  • Prioritizing statistical power and effect size is essential for improving the quality and efficiency of scientific research.
  • Adopting these recommendations can lead to more rigorous and reproducible scientific outcomes.