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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2016-09-01
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| Series: | Journal of Official Statistics |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jos-2016-0033 |