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A composite class of estimators using scrambled response mechanism for sensitive population mean in successive sampling

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  • Kumari Priyanka
  • Pidugu Trisandhya

Abstract

This paper considers the problem of estimation of population mean of a sensitive characteristics using non-sensitive auxiliary variable at current move in two move successive sampling. The proposed estimator is studied under five different scrambled response models. Various estimators have been elaborated to be the member of the proposed class of estimators. The properties of the proposed estimators have been analysed. Many estimators belonging to the proposed class have been explored under five scrambled response models. In order to identify the scrambled model effect, the proposed composite class of estimators is compared to the direct methods. Respondents privacy protection have also been elaborated under different models. Theoretical results are supplemented with numerical demonstrations using real data. Simulation has been carried out to show the applicability of proposed estimators and hence suitable recommendations are forwarded.

Suggested Citation

  • Kumari Priyanka & Pidugu Trisandhya, 2019. "A composite class of estimators using scrambled response mechanism for sensitive population mean in successive sampling," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(4), pages 1009-1032, February.
    • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:4:p:1009-1032
    DOI: 10.1080/03610926.2017.1422762
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