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Use of generalized randomized response model for enhancement of finite population variance: A simulation approach

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  • Javid Shabbir
  • Zabihullah Movaheedi

Abstract

Gupta et al. suggested an improved estimator by using the Diana and Perri model in estimating the finite population variance using the single auxiliary variable. On the same lines, Saleem et al. proposed a new scrambled randomized response model (RRT) based on two auxiliary variables for estimating the finite population variance. Recently Azeem et al. presented a new randomized response model in estimating the finite population variance. It is observed that Bias and MSE of these estimators up to first order of approximation seem to lack sufficient information. In this study, we rectify the bias and MSE expressions of the estimators proposed by Gupta et al., Saleem et al. and Azeem et al. Additionally, we suggest a new generalized class of estimators that is more efficient in comparison to the previously considered estimators. A simulation study is conducted to establish the behavior of the estimators. The suggested estimator performs better than the estimators considered by the authors earlier.

Suggested Citation

  • Javid Shabbir & Zabihullah Movaheedi, 2024. "Use of generalized randomized response model for enhancement of finite population variance: A simulation approach," PLOS ONE, Public Library of Science, vol. 19(12), pages 1-21, December.
    • Handle: RePEc:plo:pone00:0315658
    DOI: 10.1371/journal.pone.0315658
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    References listed on IDEAS

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    1. Giancarlo Diana & Pier Perri, 2011. "A class of estimators for quantitative sensitive data," Statistical Papers, Springer, vol. 52(3), pages 633-650, August.
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