Robustness of clustering methods for identification of potential falsifications in survey data - Research portal of Justus Liebig University Giessen:

Working paper/research report

Robustness of clustering methods for identification of potential falsifications in survey data

Authors list: Storfinger, Nina; Winker, Peter

Publication year: 2011

DOI Link: https://doi.org/10.22029/jlupub-5819

Title of series: Discussion papers, Zentrum für Internationale Entwicklungs- und Umweltforschung

Number in series: 57

Abstract:

Falsifications of survey data might result in specific statistical properties of the generated data differing from those of the surveyed population. Clustering methods have been proposed to identify potential falsifications based on such indicators. As any statistical procedure, the classification might entail errors, i.e. misclassification of honest interviewers as potential falsifiers and failing to identify all falsifications as such. Typically, the robustness of a statistical classification procedure is studied using a large number of problem instances with known allocation to the groups. However, given the sensitivity of falsifications in survey data, the access to datasets comprising correctly identified falsifications is very limited. Consequently, a bootstrap based approach is introduced and applied to assess the clustering method. This approach also allows modifying settings such as number of interviews per interviewer or share of falsifications in the dataset and to study the impact of these settings on the quality of the assignments. Results based on a small real dataset with identified falsifications are reported.

Authors/Editors

- Uni.-Prof. Dr. Peter Winker

Citation Styles

Harvard Citation style: Storfinger, N. and Winker, P. (2011) Robustness of clustering methods for identification of potential falsifications in survey data. (Discussion papers, Zentrum für Internationale Entwicklungs- und Umweltforschung, 57). Gießen: Zentrum für Internationale Entwicklungs- und Umweltforschung (ZEU). https://doi.org/10.22029/jlupub-5819

APA Citation style: Storfinger, N., & Winker, P. (2011). Robustness of clustering methods for identification of potential falsifications in survey data. (Discussion papers, Zentrum für Internationale Entwicklungs- und Umweltforschung, 57). Zentrum für Internationale Entwicklungs- und Umweltforschung (ZEU). https://doi.org/10.22029/jlupub-5819