Just Post It: The Lesson from Two Cases of Fabricated Data Detected by Statistics Alone

31 Pages Posted: 22 Jul 2012 Last revised: 3 Aug 2015

Uri Simonsohn

University of Pennsylvania - The Wharton School

Date Written: January 29, 2013

Abstract

I argue that requiring authors to post the raw data supporting their published results has, among many other benefits, that of making fraud much less likely to go undetected. I illustrate this point by describing two cases of fraud I identified exclusively through statistical analysis of reported means and standard deviations. Analyses of the raw data behind these provided invaluable confirmation of the initial suspicions, ruling out benign explanations (e.g., reporting errors, unusual distributions), identifying additional signs of fabrication, and also ruling out one of the suspected fraudster’s explanations for his anomalous results.

Keywords: Data transparency, fake data, science, judgment and decision making

Suggested Citation

Simonsohn, Uri, Just Post It: The Lesson from Two Cases of Fabricated Data Detected by Statistics Alone (January 29, 2013). Available at SSRN: https://ssrn.com/abstract=2114571 or http://dx.doi.org/10.2139/ssrn.2114571

Uri Simonsohn (Contact Author)

University of Pennsylvania - The Wharton School ( email )

3730 Walnut Street
JMHH 500
Philadelphia, PA 19104-6365
United States

Paper statistics

Downloads
8,274
Rank
461
Abstract Views
29,598