Open AccessSTATISTICS, BIOMEDICINE AND SCIENTIFIC FRAUD
Author(s) -
Claudio De Felice,
Alessio Cortelazzo,
S. Leoncini,
C. Signorini,
J. Hayek,
L. Ciccoli
Publication year - 2016
Publication title -
journal of the siena academy of sciences
Language(s) - English
Resource type - Journals
eISSN - 2279-882X
pISSN - 2279-8811
DOI - 10.4081/jsas.2015.6411
Subject(s) - scientific misconduct , data science , biomedicine , statistical power , computer science , statistical hypothesis testing , statistics , psychology , medicine , mathematics , alternative medicine , pathology , biology , genetics
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.