Andrés Pagán, Senior Associate Editor
November 2025Clear statistical reporting is essential for credible scientific writing. Nonetheless, many manuscripts underperform at this step, methods are sound, but the reporting is vague or incomplete. The Statistical Analyses and Methods in the Published Literature (SAMPL) guidelines were created to help authors communicate their analyses clearly and consistently, while improving transparency and reproducibility. If you’re preparing a biomedical or clinical research paper, applying SAMPL can make your submission stronger and more publication-ready.
What Are the SAMPL Guidelines?
The SAMPL Guidelines provide practical recommendations for reporting statistical methods and results in scientific articles. Unlike other frameworks that focus on study design, SAMPL focuses specifically on how to describe the analyses once they are complete. The guidelines are concise, free to access through the EQUATOR Network, and relevant to nearly all fields of biomedical research.
Why Statistical Reporting Matters
Even robust analyses can lose credibility if they are poorly reported. Readers and reviewers need to understand what tests were performed, why they were chosen, and how assumptions were checked. Applying SAMPL ensures:
• Transparency: Readers can easily follow your analytical process.
• Reproducibility: Others can replicate or verify your results.
• Editorial clarity: Reviewers spend less time questioning your methods.
In short, SAMPL helps you present your results with confidence and clarity.
• Reproducibility: Others can replicate or verify your results.
• Editorial clarity: Reviewers spend less time questioning your methods.
Key Recommendations
SAMPL offers straightforward advice for the most common statistical procedures. These include:
• Descriptive statistics: Means, medians, standard deviations, counts, and percentages.
• Comparative analyses: t-tests, ANOVA, chi-square, and non-parametric tests.
• Associations and regression: Correlations, linear and logistic regression, multivariate models.
• Effect measures: Relative risk, odds ratio, and confidence intervals.
The guidelines also remind authors to name the statistical software and version used, explain how missing data were handled, and describe any assumption checks or data transformations. These details, though simple, are often overlooked.
• Comparative analyses: t-tests, ANOVA, chi-square, and non-parametric tests.
• Associations and regression: Correlations, linear and logistic regression, multivariate models.
• Effect measures: Relative risk, odds ratio, and confidence intervals.
A Practical Tool for Authors
SAMPL complements other reporting frameworks and is increasingly recognized by journals and editors. Using it as a checklist during manuscript preparation can streamline peer review and strengthen your paper’s presentation. Ultimately, high-quality statistical reporting is not just a formality, it reflects the integrity of your research. By incorporating SAMPL into your writing process, you ensure your analyses are communicated clearly and that your methods are reproducible and in line with international standards.
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