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Benford's LawTheory and Applications$
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Steven J. Miller

Print publication date: 2015

Print ISBN-13: 9780691147611

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691147611.001.0001

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Generalizing Benfordʼs Law

Generalizing Benfordʼs Law

Chapter:
(p.304) Chapter Seventeen Generalizing Benfordʼs Law
Source:
Benford's Law
Author(s):

Joanne Lee

Wendy K. Tam Cho

George Judge

Publisher:
Princeton University Press
DOI:10.23943/princeton/9780691147611.003.0017

This chapter examines and searches for evidence of fraud in two clinical data sets from a highly publicized case of scientific misconduct. In this case, data were falsified by Eric Poehlman, a faculty member at the University of Vermont, who pleaded guilty to fabricating more than a decade of data, some connected to federal grants from the National Institutes of Health. Poehlman had authored influential studies on many topics; including obesity, menopause, lipids, and aging. The chapter's classical Benford analysis along with a presentation of a more general class of Benford-like distributions highlights interesting insights into this and similar cases. In addition, this chapter demonstrates how information-theoretic methods and other data-adaptive methods are promising tools for generating benchmark distributions of first significant digits (FSDs) and examining data sets for departures from expectations.

Keywords:   fraud, scientific misconduct, Eric Poehlman, Benford analysis, information-theoretic methods, data-adaptive methods, first significant digits, FSDs

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