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Clinical data serve as a necessary basis for medical decisions. Consequently, the importance of methods that help officials quickly identify human tampering of data cannot be underestimated. In this paper, we suggest Benford’s Law as a basis for objectively identifying the presence of experimenter distortions in the outcome of clinical research data. We test this tool on a clinical data set that contains falsified data and discuss the implications of using this and information-theoretic methods as a basis for identifying data manipulation and fraud.

Keywords: data collection ; data analysis ; research ; Benford's Law

Subject(s): Health Economics and Policy

Research and Development/Tech Change/Emerging Technologies

Issue Date: 2008-12

Publication Type: Working or Discussion Paper

PURL Identifier:

Total Pages: 8 p

Series Statement: CUDARE Working Papers


Record appears in: University of California, Berkeley > Department of Agricultural and Resource Economics > CUDARE Working Papers

Autor: Lee, Joanne ; Judge, George G.


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