Abstract
David Swanson, Moon Jung Cho, and John L. Eltinge
(2003) "Detecting Possibly Fraudulent or Error-Prone Survey Data Using Benford's Law."
Proceedings of the Section on Survey Research Methods, 2003, American
Statistical Association.
The quality of any survey's results depends on the ability to collect
data that accurately represent the underlying phenomena of interest. In
some interview surveys two potential problems with data collection are
inaccurate reporting by the respondent, and fabrication of data by a data
collector who does not contact the selected sample unit (a process called
curbstoning). For each of these cases, one may be able to identify
problematic interviews by evaluating the distribution of the leading
digits of the responses to the questionnaire. In the aggregate, the
distribution tends to follow a pattern known as Benford's Law.
Consequently, it may be appropriate to re-interview the cases that display
a markedly different distribution of leading digits. This paper describes
a potential application of this idea to the Consumer Expenditure Interview
Survey.
Last Modified Date: July 16, 2004
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