Heart Podcast Top 10 statistical errors in submitted papers...and how to avoid them
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Oct 7, 2025 Dan Green, a Senior Teaching Fellow at Aston University and a statistical reviewer, shares invaluable insights into common statistical errors found in submitted manuscripts. He discusses the importance of avoiding incorrect causal language and emphasizes the need for well-structured abstracts. Green highlights tips on reporting statistical analyses accurately, utilizing clear participant flow diagrams, and avoiding pitfalls in regression modeling. He also advises against relying solely on univariable p-values for model building, promoting transparency in reporting missing data.
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Format Abstracts To Journal Requirements
- Follow the journal's abstract structure and include the five W's: what, who, where, when and why.
- Compare your abstract to published articles in the same journal to ensure completeness.
Don't Reveal Results In Methods
- Keep results out of the methods section and describe only planned procedures in methods.
- Read your draft and ensure you haven't revealed findings before the results section.
Describe All Statistical Analyses Clearly
- Describe every analysis you report: descriptive stats, hypothesis tests, regression and sensitivity analyses.
- Create matching bullet lists for planned analyses in methods and actual analyses in results to avoid surprises.