Improved mean estimation of sensitive study variable under two phase sampling with sub-sampling the non-respondents
Hafiza Fakarul NisaFakharunnisa153@gmail.comDepartment of StatisticsLahore College for Women UniversityLahore, PakistanView full profile → , *Sadia KhalilCorresponding authors_khali2@uncg.eduSadia.Khalil@icwu.edu.pkAffiliation 1Department of StatisticsLahore College for Women UniversityLahore, PakistanAffiliation 2Department of Mathematics and StatisticsUniversity of North CarolinaGreensboro, U.S.A.View full profile → , Sat Guptasngupta@uncg.eduDepartment of Mathematics and StatisticsUniversity of North CarolinaGreensboro, U.S.A.View full profile →
* Corresponding author · click or hover a name for details
- Received:
- 07 Dec 2022
- Published Online:
- 01 Aug 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIM-1743
- Pages:
- 1735–1758
Abstract
Keywords
Subject Classifications
References
[1] J. Neyman, “Contribution to the theory of sampling human populations,” Journal of the American Statistical Association, vol. 33, no. 201, pp. 101–116 (1938).
[2] S. L. Warner, “Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias,” Journal of the American Statistical Association, vol. 60, no. 309, pp. 63–69 (1965).
[3] B. H. Eichhorn and L. S. Hayre, “Scrambled randomized response methods for obtaining sensitive quantitative data,” Journal of Statistical Planning and Inference, vol. 7, no. 4, pp. 307–316 (1983).
[4] S. Gupta, B. Gupta, and S. Singh, “Estimation of sensitivity level of personal interview survey questions,” Journal of Statistical Planning and Inference, vol. 100, no. 2, pp. 239–247 (2002).
[5] S. Gupta and J. Shabbir, “Sensitivity Estimation for Personal Interview Survey Questions,” Statistica, vol. 64, no. 4, pp. 643–653 (2004).
[6] R. Sousa, J. Shabbir, P. C. Real, and S. Gupta, “Ratio Estimation of the Mean of a Sensitive Variable in the Presence of Auxiliary Information,” Journal of Statistical Theory and Practice, vol. 4, no. 3, pp. 495–507 (2010).
[7] S. Gupta, J. Shabbir, R. Sousa, and P. Corte-Real, “Estimation of the Mean of a Sensitive Variable in the Presence of Auxiliary Information,” Communications in Statistics-Theory and Methods, vol. 41, no. 13-14, pp. 2394–2404 (2012).
[8] S. Gupta, J. Shabbir, R. Sousa, and P. Corte-Real, “Improved Exponential Type Estimators of the Mean of a Sensitive Variable in the Presence of Non-sensitive Auxiliary Information,” Communications in Statistics-Simulation and Computation, vol. 45, no. 9, pp. 3317–3328 (2016).
[9] M. H. Hansen and W. N. Hurwitz, “The problem of non-response in sample surveys,” Journal of the American Statistical Association, vol. 41, no. 236, pp. 517–529 (1946).
[10] M. Kumar, R. Singh, A. K. Singh, and F. Smarandache, “Some ratio type estimators under measurement errors,” World Applied Sciences Journal, vol. 14, no. 2, pp. 272–276 (2011).
[11] S. Khalil, M. Noor-ul-Amin, and M. Hanif, “Estimation of population mean for a sensitive variable in the presence of measurement error,” Journal of Statistics and Management Systems, vol. 21, no. 1, pp. 81–91 (2018).
[12] N. Singh, G. K. Vishwakarma, and J. M. Kim, “Computing the effect of measurement error on efficient variant of the product and ratio estimator using auxiliary variable,” Communications in Statistics-Simulation and Computation, vol. 51, no. 2, pp. 604–625 (2019).
[13] S. R. Singh and P. Sharma, “Method of estimation in the presence of non-response and measurement errors simultaneously,” Journal of Modern Applied Statistical Methods, vol. 14, no. 1, pp. 107–121 (2015).
[14] N. Singh and G. K. Vishwakarma, “A generalized class of estimator of population mean with the combined effect of measurement errors and non-response in sample survey,” Revista Investigacion Operacional, vol. 40, no. 2, pp. 275–285 (2019).
[15] A. Audu, R. Singh, S. Khare, and N. S. Dauran, “Almost unbiased estimators for population mean in the presence of non-response and measurement error,” Journal of Statistics and Management Systems, vol. 24, no. 3, pp. 573–589 (2021).
[16] S. Khalil, Q. Zhang, and S. Gupta, “Mean estimation of sensitive variables under measurement errors using optional RRT models,” Communications in Statistics-Simulation and Computation, vol. 50, no. 5, pp. 1417–1426 (2021).
[17] S. Khalil, M. Noor-ul-Amin, and M. Hanif, “Generalized estimator of population mean by using conventional and non-conventional measures in the presence of measurement errors,” Communications in Statistics-Simulation and Computation, vol. 48, no. 2, pp. 516–529 (2019).
[18] Q. Zhang, S. Gupta, G. Kalucha, and S. Khalil, “Ratio estimation of the mean under RRT models,” Journal of Statistics and Management Systems, vol. 22, no. 1, pp. 97–113 (2019).
[19] Q. Zhang, S. Khalil, and S. Gupta, “Mean estimation of sensitive variables under non-response and measurement errors using optional RRT models,” Journal of Statistical Theory and Practice, vol. 15, no. 3, pp. 1–15 (2021).
[20] U. Shuja, S. Khalil, and S. Gupta, “Mean estimation using scrambled responses with the impact of measurement errors in two-phase sampling,” Journal of Interdisciplinary Mathematics, vol. 25, no. 6, pp. 1675–1695 (2022).
[21] G. Diana and P. F. Perri, “A class of estimators for quantitative sensitive data,” Stat Papers, vol. 52, pp. 633–650 (2011).
[22] S. Gupta, S. Mehta, J. Shabbir, and S. Khalil, “A unified measure of respondent privacy and model efficiency in quantitative RRT models,” Journal of Statistical Theory and Practice, vol. 12, no. 3, pp. 506–511 (2018).
[23] Z. Yan, J. Wang, and J. Lai, “An efficiency and protection degree-based comparison among the quantitative randomized response strategies,” Communications in Statistics: Theory and Methods, vol. 38, no. 3, pp. 400–408 (2009).
[24] G. Diana, S. Riaz, and J. Shabbir, “Hansen and Hurwitz estimator with scrambled response on the second call,” Journal of Applied Statistics, vol. 41, no. 3, pp. 596–611 (2014).
