A statistical approach to detect cheating interviewers
AbstractSurvey 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. --
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Bibliographic InfoPaper provided by Justus Liebig University Giessen, Center for international Development and Environmental Research (ZEU) in its series Discussion Papers with number 39.
Date of creation: 2008
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cheating interviewers; Benford's law; cluster analysis; data fabrication;
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