IDEAS home Printed from https://ideas.repec.org/p/zbw/zeudps/39.html
   My bibliography  Save this paper

A statistical approach to detect cheating interviewers

Author

Listed:
  • Bredl, Sebastian
  • Winker, Peter
  • Kötschau, Kerstin

Abstract

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.

Suggested Citation

  • Bredl, Sebastian & Winker, Peter & Kötschau, Kerstin, 2008. "A statistical approach to detect cheating interviewers," Discussion Papers 39, Justus Liebig University Giessen, Center for international Development and Environmental Research (ZEU).
  • Handle: RePEc:zbw:zeudps:39
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/39808/1/593464877.pdf
    Download Restriction: no

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Josten Michael & Trappmann Mark, 2016. "Interviewer Effects on a Network-Size Filter Question," Journal of Official Statistics, De Gruyter Open, vol. 32(2), pages 349-373, June.
    2. De Haas Samuel & Winker Peter, 2016. "Detecting Fraudulent Interviewers by Improved Clustering Methods – The Case of Falsifications of Answers to Parts of a Questionnaire," Journal of Official Statistics, De Gruyter Open, vol. 32(3), pages 643-660, September.
    3. Schräpler Jörg-Peter, 2011. "Benford’s Law as an Instrument for Fraud Detection in Surveys Using the Data of the Socio-Economic Panel (SOEP)," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(5-6), pages 685-718, October.
    4. Michael Spagat, 2010. "Estimating the Human Costs of War: The Sample Survey Approach," HiCN Research Design Notes 14, Households in Conflict Network.
    5. Finn, Arden & Ranchhod, Vimal, 2013. "Genuine Fakes: The prevalence and implications of fieldworker fraud in a large South African survey," SALDRU Working Papers 115, Southern Africa Labour and Development Research Unit, University of Cape Town.
    6. Storfinger, Nina & Winker, Peter, 2011. "Robustness of clustering methods for identification of potential falsifications in survey data," Discussion Papers 57, Justus Liebig University Giessen, Center for international Development and Environmental Research (ZEU).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:zeudps:39. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - German National Library of Economics). General contact details of provider: http://edirc.repec.org/data/zegiede.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.