Statistical Data Editing in Scientific Articles.
10.3346/jkms.2017.32.7.1072
- Author:
Farrokh HABIBZADEH
1
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Author Information
1. Past President, World Association of Medical Editors
2. Founder and Editor, The International Journal of Occupational and Environmental Medicine (The IJOEM)
3. Adjunct Professor, Shiraz University of Medical Sciences, Shiraz, Iran
4. Managing Director, R&D Head
- Publication Type:Review
- Keywords:
Journalism;
Editorial Policies;
Peer Review;
Statistics;
Normal Distribution;
Confidence Intervals
- MeSH:
Confidence Intervals;
Editorial Policies;
Journalism;
Normal Distribution;
Peer Review;
Publications;
Research Design;
Research Report
- From:Journal of Korean Medical Science
2017;32(7):1072-1076
- CountryRepublic of Korea
- Language:English
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Abstract:
Scientific journals are important scholarly forums for sharing research findings. Editors have important roles in safeguarding standards of scientific publication and should be familiar with correct presentation of results, among other core competencies. Editors do not have access to the raw data and should thus rely on clues in the submitted manuscripts. To identify probable errors, they should look for inconsistencies in presented results. Common statistical problems that can be picked up by a knowledgeable manuscript editor are discussed in this article. Manuscripts should contain a detailed section on statistical analyses of the data. Numbers should be reported with appropriate precisions. Standard error of the mean (SEM) should not be reported as an index of data dispersion. Mean (standard deviation [SD]) and median (interquartile range [IQR]) should be used for description of normally and non-normally distributed data, respectively. If possible, it is better to report 95% confidence interval (CI) for statistics, at least for main outcome variables. And, P values should be presented, and interpreted with caution, if there is a hypothesis. To advance knowledge and skills of their members, associations of journal editors are better to develop training courses on basic statistics and research methodology for non-experts. This would in turn improve research reporting and safeguard the body of scientific evidence.
