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Ethics of Data Analysis

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Abstract

Research is the process of methodically gathering and analyzing new information on a topic, in order to generate more reliable knowledge about the world. The data that is gathered in research is often not accessible to other people reading the final reports and is only rarely reviewed by anyone else even when it is available. Because most readers of research reports do not have the time or even access to review the raw data from the research themselves, they place their trust in the authors of the report that the results refer to accurate data from research that truly took place as described. Thus the knowledge gained and shared from research depends critically on a system of social trust in the veracity of the data and results. So the ethics of data analysis concerns two major forms of research misconduct – fabrication of data or results and falsification of data or results – as well as the minor practical issue of preserving the data for future reexamination.

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References

  1. Fanelli D. How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data. PLoS One. 2009; 4: e5738.

    Article  Google Scholar 

  2. Carlisle JB. Data fabrication and other reasons for non-random sampling in 5087 randomised, controlled trials in anaesthetic and general medical journals. Anaesthesia. 2017; 72: 944-952.

    Article  CAS  Google Scholar 

  3. Kingori P, Gerrets R. Morals, morale and motivations in data fabrication: Medical research fieldworkers views and practices in two Sub-Saharan African contexts. Soc Sci Med. 2016; 166: 150-159.

    Article  Google Scholar 

  4. Steen RG. Retractions in the scientific literature: do authors deliberately commit research fraud? J Med Ethics. 2011; 37: 113-117.

    Article  Google Scholar 

  5. Baerlocher MO, O’Brien J, Newton M, Gautam T, Noble J. Data integrity, reliability and fraud in medical research. Eur J Intern Med. 2010; 21: 40-45.

    Article  Google Scholar 

  6. Koshland DE Jr. Fraud in Science. Science. 1987; 235: 141.

    Google Scholar 

  7. Kennedy D. Multiple Authors, Multiple Problems. Science. 2003; 301: 733.

    Article  CAS  Google Scholar 

  8. Golder S, Loke YK, Wright K, Norman G. Reporting of Adverse Events in Published and Unpublished Studies of Health Care: A Systematic Review. PLoS Med. 2016; 13: e1002127.

    Article  Google Scholar 

  9. Haidich A-B, Birtsou C, Dardavessis T, Tirodimos I, Arvanitidou M. The quality of safety reporting in trials is still suboptimal: Survey of major general medical journals. J Clin Epidemiol. 2011; 64: 124-135.

    Article  Google Scholar 

  10. Bailar JC III. Science, Statistics, and Deception. Ann Intern Med. 1986; 104: 259-260.

    Article  Google Scholar 

  11. Sigma Xi. Honor in Science. Research Triangle Park, NC, USA: Sigma Xi; 2000.

    Google Scholar 

  12. Altman DG. Practical Statistics for Medical Research. Boca Raton, FL, USA: CRC Press; 1991, 1999.

    Google Scholar 

  13. Gross RA. Style, spin, and science. Neurology. 2015; 85: 10-11.

    Article  Google Scholar 

  14. Lazarus C, Haneef R, Ravaud P, Boutron I. Classification and prevalence of spin in abstracts of non-randomized studies evaluating an intervention. BMC Med Res Methodol. 2015; 15: 85.

    Article  Google Scholar 

  15. Chiu K, Grundy Q, Bero L. ‘Spin’ in published biomedical literature: A methodological systematic review. PLoS Biol. 2017; 15: e2002173.

    Article  Google Scholar 

  16. A picture worth a thousand words (of explanation). Nat Methods. 2006; 3: 237.

    Google Scholar 

  17. International Committee of Medical Journal Editors. Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals. Philadelphia: American College of Physicians; 1978, 2017. Accessed on 12 January 2018 at: www.icmje.org/icmje-recommendations.pdf

  18. Organisation for Economic Co-Operation and Development, Global Science Forum. Best Practices for Ensuring Scientific Integrity and Preventing Misconduct. Accessed on 13 January 2018 at: www.oecd.org/science/inno/40188303.pdf

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Hanna, M. (2019). Ethics of Data Analysis. In: How to Write Better Medical Papers. Springer, Cham. https://doi.org/10.1007/978-3-030-02955-5_11

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  • DOI: https://doi.org/10.1007/978-3-030-02955-5_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02954-8

  • Online ISBN: 978-3-030-02955-5

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