Statistical Reporting Standards
Transparent reporting of statistical results—including effect sizes, confidence intervals, p-values, and assumptions—is essential for scientific integrity and reproducibility. Many published studies report p-values in isolation without effect sizes or confidence intervals, making it impossible for readers to assess the magnitude of findings. Statistical reporting standards, emphasized by Cumming (2013), the American Statistical Association, and the ICMJE, require effect sizes, confidence intervals, and discussion of uncertainty. This enables readers to judge whether findings are practically significant (not just statistically significant) and to compare effect sizes across studies in meta-analyses. Poor statistical reporting wastes research and prevents proper synthesis of evidence.
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- Cumming, G. (2013). The new statistics: Why and how. Psychological Science, 25(1), 7–29. · DOI 10.1177/0956797613504966
- Fidler, F., Thomason, N., Cumming, G., Finch, S., & Leeman, J. (2005). Editors can lead researchers to confidence intervals, but can't make them think: Statistical reform lessons from medicine. Psychological Science, 15(2), 119–126. · DOI 10.1111/j.0963-7214.2004.01502008.x
- International Committee of Medical Journal Editors (2023). Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals. · URL
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