STATISTICS, BIOMEDICINE AND SCIENTIFIC FRAUD

  • C. De Felice | c.defelice@ao-siena.toscana.it Neonatal Intensive Care Unit, University Hospital, Azienda Ospedaliera Universitaria Senese (AOUS), Policlinico “S. M. alle Scotte”, Siena, Italy.
  • A. Cortelazzo Department of Medical Biotechnologies, University of Siena; Child Neuropsychiatry Unit, University Hospital, (AOUS), Policlinico “S.M. alle Scotte”, Siena, Italy.
  • S. Leoncini Child Neuropsychiatry Unit, University Hospital, (AOUS), Policlinico “S.M. alle Scotte”, Siena; Department of Molecular and Developmental Medicine, University of Siena, Italy.
  • C. Signorini Department of Molecular and Developmental Medicine, University of Siena, Italy.
  • J. Hayek Child Neuropsychiatry Unit, University Hospital, (AOUS), Policlinico “S.M. alle Scotte”, Siena, Italy.
  • L. Ciccoli Department of Molecular and Developmental Medicine, University of Siena, Italy.

Abstract

A consistent fraction of published data on scientific journals is not reproducible mainly due to insufficient knowledge of statistical methods. Here, we discuss on the use of proper statistical tools in biomedical research and statistical pitfalls potentially undermining the scientific validity of published data. Apart from unaware errors, a growing concern exists regarding data fabrication and scientific misconduct. Indeed, the social impact of false scientific data can be largely unpredictable and devastating, as shown by the worldwide dramatic effects on vaccinations coverage following a retracted paper published on a highly authoritative medical journal. Unfortunately, statistics shows a quite limited power in detecting false science, although a few statistical tools, such as the Benford’s law, are known. Taken together, statistics in biomedical sciences i) is a powerful tool to interpret experimental data; ii) has limited power in detecting false science; and iii) first and foremost, is not the result of a simple “click of a mouse”, but should be the result of accurate research planning by experienced and knowledgeable users.

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Published
2016-12-13
Info
Issue
Section
Focus on Biostatistics
Keywords:
Biomedical sciences, scientific fraud, scientific misconduct, statistics, statistical errors, statistical inference
Statistics
  • Abstract views: 1130

  • PDF: 474
How to Cite
De Felice, C., Cortelazzo, A., Leoncini, S., Signorini, C., Hayek, J., & Ciccoli, L. (2016). STATISTICS, BIOMEDICINE AND SCIENTIFIC FRAUD. Journal of the Siena Academy of Sciences, 7(1). https://doi.org/10.4081/jsas.2015.6411