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Use of appropriate statistical tools in biomedical research: Current trend & status
Anup Kumar1, Jai Kishun1, Uttam Singh1
1Department of Biostatistics & Health Informatics, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Biomedical research articles often contain statistical errors, leading to unreliable results. Improving statistical application and expert consultation is crucial for accurate data interpretation and trustworthy publications.
Area of Science:
- Biomedical Research
- Statistical Analysis
- Publication Integrity
Background:
- Published biomedical research frequently exhibits statistical errors in design, analysis, and interpretation.
- These statistical flaws can render costly research ineffective and undermine study objectives.
- Many peer-reviewed biomedical articles contain statistical errors and deficiencies.
Purpose of the Study:
- To examine the current trends and status of statistical application in biomedical research articles.
- To evaluate the use and misuse of statistical tools in published original research.
- To assess critical components like study design, sample size estimation, and statistical measures.
Main Methods:
- A review of 300 original research articles from 37 selected journals.
- Journals were sourced from major international publication groups (CLINICAL KEY, BMJ Group, WILEY, CAMBRIDGE, OXFORD).
- Articles were evaluated for study design, sample size estimation, and statistical measures.
Main Results:
- 85.3% of articles were observational, 14.7% were interventional.
- Sample size estimation was not reproducible in 93% of articles.
- Simple random sampling was rare; normality assumptions were rarely tested before parametric tests.
Conclusions:
- Engaging statistical experts is essential for reliable and precise biomedical research findings.
- Journals should implement standardized reporting rules for study design, sample size, and data analysis.
- Careful application of statistical procedures enhances reader trust and the reliability of published inferences.
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