CUDARE working paper 1073, University of California, Berkeley
ISSN / ISBN: Not available at this time
Abstract: ABSTRACT: 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 Benfordís 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
Bibtex not available at this time.
Reference Type: E-Print
Subject Area(s): Statistics