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A Statistical Approach to Provide Individualized Privacy for Surveys

Author

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  • Fernando Esponda
  • Kael Huerta
  • Victor M Guerrero

Abstract

In this paper we propose an instrument for collecting sensitive data that allows for each participant to customize the amount of information that she is comfortable revealing. Current methods adopt a uniform approach where all subjects are afforded the same privacy guarantees; however, privacy is a highly subjective property with intermediate points between total disclosure and non-disclosure: each respondent has a different criterion regarding the sensitivity of a particular topic. The method we propose empowers respondents in this respect while still allowing for the discovery of interesting findings through the application of well-known inferential procedures.

Suggested Citation

  • Fernando Esponda & Kael Huerta & Victor M Guerrero, 2016. "A Statistical Approach to Provide Individualized Privacy for Surveys," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-14, January.
  • Handle: RePEc:plo:pone00:0147314
    DOI: 10.1371/journal.pone.0147314
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    Cited by:

    1. Andreas Lagerås & Mathias Lindholm, 2020. "How to ask sensitive multiple‐choice questions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(2), pages 397-424, June.

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