Vom Finanz- zum Wissenschaftsbetrug

Abstract

Fraud is as old as Mankind. There are an enormous number of historical documents which show the interaction between truth and untruth; therefore it is not really surprising that the prevalence of publication discrepancies is increasing. More surprising is that new cases especially in the medical field generate such a huge astonishment. In financial mathematics a statistical tool for detection of fraud is known which uses the knowledge of Newcomb and Benford regarding the distribution of natural numbers. This distribution is not equal and lower numbers are more likely to be detected compared to higher ones. In this investigation all numbers contained in the blinded abstracts of the 2009 annual meeting of the Swiss Society of Anesthesia and Resuscitation (SGAR) were recorded and analyzed regarding the distribution. A manipulated abstract was also included in the investigation. The χ(2)-test was used to determine statistical differences between expected and observed counts of numbers. There was also a faked abstract integrated in the investigation. A p<0.05 was considered significant. The distribution of the 1,800 numbers in the 77 submitted abstracts followed Benford's law. The manipulated abstract was detected by statistical means (difference in expected versus observed p<0.05). Statistics cannot prove whether the content is true or not but can give some serious hints to look into the details in such conspicuous material. These are the first results of a test for the distribution of numbers presented in medical research.

Scientific fraud in 20 falsified anesthesia papers

“…Deviations from the expected digit frequencies provoke detailed analysis of data by tax authorities [17,18,20,27]. Until now this law has not been used for the statistical review of data extracted from medical papers although abstracts were recently investigated [21].…”

“…Fabricating or distorting data for publication are fraudulent actions that may have different motivations, such as enhancement of prestige, influence or income. Financial auditors and tax authorities use statistical methods for data analysis to detect fraud based on the observations described by Newcomb and Benford [2,11,12,16] and numbers from natural sources show a counter-intuitive frequency distribution, which has also been shown for medical data [21]. According to Benford's law the digit 1 appears as the leading number to the left of the decimal point more often compared to digits 2-9.…”

“…The present study investigates for the first time, whether these studies can be detected as false using the method described by Benford and Newcomb. To the best of the authors' knowledge, although this law was formulated in the late nineteenth century it has not yet been used to assess data from medical studies except medical abstracts [21]. Therefore, an attempt was made to identify known falsified examples of medical papers by mathematical analyses based on Benford's law.…”

Investigating and preventing scientific misconduct using Benford’s Law

“…We propose that Benford's Law might provide a useful next step in the investigative process [15]. Analysing the distribution frequency of financial data with reference to Benford's Law is a well-established fraud analysis technique in the practice of professional auditing [16], and its effectiveness has been shown in detecting fabricated data for example in the fields of anaesthesia, sociology and accounting research ( [17][18][19][20][21]; see also [22] where it was not effective for a group of social psychology studies, although we explain later why detection can depend on careful choice of test statistic).…”