Don't Get Duped: Fraud through Duplication in Public Opinion Surveys

Statistical Journal of the IAOS, Forthcoming

28 Pages Posted: 20 Mar 2015 Last revised: 23 Feb 2016

See all articles by Noble Kuriakose

Noble Kuriakose

SurveyMonkey

Michael Robbins

University of Michigan at Ann Arbor; Princeton University - Department of Political Science

Date Written: December 12, 2015

Abstract

Fraud in survey research can take many forms, but a common form is through duplication of valid interviews. Duplication of a valid interview has a number of advantages: expected relationships between the variables will hold across the data set and, if done across a number of interviews, this approach can evade many standard techniques to detect fraud such as straight-lining analysis and the application of Benford's law. In this paper, we consider the likelihood of encountering near duplicates in survey data, suggest methods to fingerprint suspicious observations, report on our analysis of over 1,000 publicly available survey datasets and argue that nearly one in five widely used country-year surveys surveys from major international data sets have exact or near duplicates in excess of 5% of observations.

Keywords: survey research, duplicates, near duplicates, survey methodology, curb stoning, falsification, fraud, surveys

Suggested Citation

Kuriakose, Noble and Robbins, Michael, Don't Get Duped: Fraud through Duplication in Public Opinion Surveys (December 12, 2015). Statistical Journal of the IAOS, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2580502

Noble Kuriakose (Contact Author)

SurveyMonkey ( email )

101 Lytton Avenue
Palo Alto, CA 94301
United States

Michael Robbins

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

Princeton University - Department of Political Science ( email )

Corwin Hall
Princeton, NJ 08544-1012
United States

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