Stanford Webinar: How to Be a Statistical Detective | Summary and Q&A

TL;DR
Learn how to identify and catch statistical errors in medical literature using common sense and online tools.
Key Insights
- đˇ Statistical errors are common in medical literature, and being able to detect and correct them is crucial for accurate and reliable research.
- đ¨ Simple numerical mistakes and data manipulation errors can have serious consequences in patient care.
- đĻģ Online tools can help identify inconsistencies and extract data from graphs, aiding in the verification of statistical results.
Transcript
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Questions & Answers
Q: Why is it important to be a statistical detective in the medical field?
Being a statistical detective is crucial in the medical field because many papers have statistical errors that can affect patient care and treatment outcomes.
Q: What are some common types of statistical errors found in medical literature?
Common errors include numerical mistakes, data manipulation, improper statistical comparisons, and misinterpretation of results.
Q: What are some online tools that can help catch statistical errors?
Some useful online tools include checkers like "That Check," "Statcheck," and "WebPlotDigitizer" that help identify inconsistencies in statistical reporting and extract underlying raw data from graphs.
Q: Is pre-registering studies and making data publicly available effective in addressing the reproducibility crisis?
Yes, pre-registering studies and sharing data publicly are initiatives that can improve transparency and reproducibility in research, allowing for better evaluation and verification of results.
Summary & Key Takeaways
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Many medical papers have statistical errors, even simple numerical mistakes, which can have serious consequences.
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Common sense, basic statistical knowledge, and online tools can help catch errors before publication or during peer review.
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Case studies demonstrate the importance of checking and understanding data, ensuring accuracy in statistical reporting, and conducting sensitivity analyses.
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