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"Interviewers have a substantial impact on data quality. Their motivation to deviate from prescribed routines is analyzed. Thereby, the focus is on falsifications of survey data. Based on approaches from cognitive psychology and principal agent theory data based indicators are constructed which should differ between real and falsified interview data. A multivariate cluster analysis is applied to a set of such indicators to identify interviewers who are more likely to have contributed falsified data and might be subject to a follow up in a fieldwork setting. A heuristic optimization algorithm is used for the clustering instead of sequential procedures. Data obtained from an experiment are used to evaluate the performance of the indicators and of the multivariate method. The experiment used two payment schemes for the interviewers - per interview and per hour. It is also analyzed to what extent the payment scheme affects interviewers' behavior with regard to falsifications."Die Autoren verwenden den ALLBUS 2008 als Vergleichsdatensatz für ihre Studie.
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ALLBUS-Bibliography
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Aufgenommen: 28. Fassung, April 2014
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?:name
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A Method for ex-post Identification of Falsifications in Survey Data
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2013
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ALLBUS
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ALLBUS2008
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ALLBUS_input2013
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ALLBUS_pro
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ALLBUS_version28
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FDZ_ALLBUS
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checked
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english
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techreport
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