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The Prevalence of Misreporting and Misinterpreting Correlation Coefficients in Biomedical Literature

Published: November 18, 2025 | arXiv ID: 2511.14092v1

By: Jiayang Xu , Xintong Chen , Yufeng Liu and more

Potential Business Impact:

Fixes how scientists measure connections between things.

Business Areas:
Clinical Trials Health Care

Correlation coefficient is widely used in biomedical and biological literature, yet its frequent misuse and misinterpretation undermine the credibility and reproducibility of the scientific findings. We systematically reviewed 1326 records of correlation analyses across 310 articles published in Science, Nature, and Nature Neuroscience in 2022. Our analysis revealed a troubling pattern of poor statistical reporting and inferring: 58.71% (95% CI: [53.23%, 64.19%], 182/310) of studies did not explicitly report sample sizes, and 98.06% (95% CI: [96.53%, 99.60%], 304/310) failed to provide confidence intervals for correlation coefficients. Among 177 articles inferring correlation strength, 45.25% (95% CI: [38.42%, 53.10%], 81/177) relied solely on point estimates, while 53.63% (95% CI: [46.90%, 61.58%], 96/177) drew conclusions based on null hypothesis significance testing. This widespread omission and misuse highlight a systematic gap in both statistic literacy and editorial standards. We advocate clear reporting guidelines mandating effect sizes and confidence intervals in correlation analyses to enhance the transparency, rigor, and reproducibility of quantitative life sciences research.

Country of Origin
🇨🇳 China

Page Count
14 pages

Category
Statistics:
Methodology