A statistical approach to detect cheating interviewers - Sebastian Bredl; Peter Winker; Kerstin Kötschau (Justus-Liebig-Universität Gießen, Zentrum für Internationale Entwicklungs- und Umweltforschung (ZEU), 2008)
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: 330; cheating interviewers; Benford's law; cluster analysis; data fabrication; Befragung; Clusteranalyse; Statistische Methode