Detecting Fraudulent Interviewers by Improved Clustering Methods – The Case of Falsifications of Answers to Parts of a Questionnaire

Falsified interviews represent a serious threat to empirical research based on survey data. The identification of such cases is important to ensure data quality. Applying cluster analysis to a set of indicators helps to identify suspicious interviewers when a substantial share of all of their interv...

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Bibliographic Details
Main Authors: De Haas Samuel, Winker Peter
Format: Article
Language:English
Published: Sciendo 2016-09-01
Series:Journal of Official Statistics
Subjects:
Online Access:https://doi.org/10.1515/jos-2016-0033