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Generalized Double Sampling Family of Estimators for Population mean of Sensitive Variable Harnessing Non-sensitive Auxiliary Variable and Attribute

Author

Listed:
  • Subhash Kumar Yadav

    (Babasaheb Bhimrao Ambedkar University)

  • Tarushree Bari

    (Babasaheb Bhimrao Ambedkar University)

  • Gajendra K. Vishwakarma

    (Indian Institute of Technology Dhanbad)

Abstract

We present an enhanced double sampling generalized type estimator for the population mean of a sensitive research variable using information gathered from non-sensitive auxiliary variables and attribute, using a two-phase sampling procedure. Some special cases of the suggested family of estimators are also discussed. The expressions for bias and mean squared error of the proposed generalized estimators are derived and theoretical comparisons are made with competing estimators. Theoretical results are supported by numerical evidence generated from real-world data. A simulation analysis is also carried out to compare the efficiencies of the proposed and competing family of esimators. Both data sets show that the proposed generalized class of estimators outperforms all other estimators currently in use.

Suggested Citation

  • Subhash Kumar Yadav & Tarushree Bari & Gajendra K. Vishwakarma, 2023. "Generalized Double Sampling Family of Estimators for Population mean of Sensitive Variable Harnessing Non-sensitive Auxiliary Variable and Attribute," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 54-76, May.
    • Handle: RePEc:spr:sankhb:v:85:y:2023:i:1:d:10.1007_s13571-022-00299-w
    DOI: 10.1007/s13571-022-00299-w
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    References listed on IDEAS

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    1. Erum Zahid & Javid Shabbir, 2019. "Estimation of finite population mean for a sensitive variable using dual auxiliary information in the presence of measurement errors," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-17, February.
    2. Iram Saleem & Aamir Sanaullah & Muhammad Hanif, 2019. "Double-sampling regression-cum-exponential estimator of the mean of a sensitive variable," Mathematical Population Studies, Taylor & Francis Journals, vol. 26(3), pages 163-182, July.
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