A statistical approach to detect cheating interviewers
Peter Winker () and
No 39, Discussion Papers from Justus Liebig University Giessen, Center for international Development and Environmental Research (ZEU)
Survey data are potentially affected by cheating interviewers. Even a small number of fabricated interviews might seriously impair the results of further empirical analysis. Besides reinterviews some statistical approaches have been proposed for identifying fabrication of interviews. As a novel toolin this context, cluster and discriminant analysis are used. Several indicators are combined to classify 'at risk' interviewers based solely on the collected data. An application to a dataset with known cases of cheating interviewers demonstrates that the methods are able to identify the cheating interviewers with a high probability. The multivariate classiffication is superior to the application of a singleindicator such as Benford's law.
Keywords: cheating interviewers; Benford's law; cluster analysis; data fabrication (search for similar items in EconPapers)
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