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Analyzing efficiency for the multi-category parallel method

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  • Heiko Groenitz

    (Philipps-University Marburg)

Abstract

Survey data play an important role in many areas. The surveys typically consist of a list of direct questions. However, if survey data on sensitive topics (tax evasion, fraud, discrimination) are desired, direct questions lead to problems in data quality by answer refusal and untruthful answers. For this reason, there is a need for clever questioning procedures which protect the privacy of the respondents and yield data that allow statistical inference. One interesting procedure for categorical sensitive characteristics is the parallel method (PM). To apply the PM, the survey agency must choose certain parameters of the PM. So far, it has been not analyzed how these PM parameters influence the estimation efficiency corresponding to the PM. This paper addresses this important issue. Our investigations result in recommendations for survey agencies on appropriate PM parameters.

Suggested Citation

  • Heiko Groenitz, 2018. "Analyzing efficiency for the multi-category parallel method," METRON, Springer;Sapienza Università di Roma, vol. 76(2), pages 231-250, August.
    • Handle: RePEc:spr:metron:v:76:y:2018:i:2:d:10.1007_s40300-017-0134-y
    DOI: 10.1007/s40300-017-0134-y
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    References listed on IDEAS

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    3. Guo-Liang Tian, 2014. "A new non-randomized response model: The parallel model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(4), pages 293-323, November.
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