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American Journal of Mathematical and Management Sciences Volume 33, 2014 - Issue 2
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Original Articles

Estimation of Finite Population Mean Using Optional RRT Models in the Presence of Nonsensitive Auxiliary Information

S. GuptaDepartment of Mathematics and Statistics, The University of North Carolina at Greensboro, Greensboro, NC27412, USACorrespondence[email protected]
,
G. KaluchaDepartment of Mathematics, University of Delhi, Delhi, 110007, India
,
J. ShabbirDepartment of Statistics, Quaid-I-Azam University, Islamabad, 45320, Pakistan
&
B. K. DassDepartment of Mathematics, University of Delhi, Delhi, 110007, India
Pages 147-159 | Published online: 02 Jun 2014

References

  • Eichhorn, B.H., & Hayre, L.S. (1983). Scrambled randomized response methods for obtaining sensitive quantitative data. Journal of Statistical Planning and Inference, 7(4), 307–316.
  • Grover, L.K., & Kaur, P. (2011). An improved estimator of the finite population mean in simple random sampling. Model Assisted Statistics and Applications, 6(1), 47–55.
  • Gupta, S., Gupta, B.C., & Singh, S. (2002). Estimation of sensitivity level of personnel interview survey questions. Journal of Statistical Planning and Inference, 100(2), 239–247.
  • Gupta, S., Mehta, S., Shabbir, J., & Dass, B.K. (2013). Generalized scrambling in quantitative optional randomized response models. Communications in Statistics—Theory and Methods, 42(20), 1–9.
  • Gupta, S., Shabbir, J., & Sehra, S. (2010). Mean and sensitivity estimation in optional randomized response models. Journal of Statistical Planning and Inference, 140(10), 2870–2874.
  • Gupta, S., Shabbir, J., Sousa, R., & Corte-Real, P. (2012). Estimation of the mean of a sensitive variable in the presence of auxiliary information. Communications in Statistics—Theory and Methods, 41(13–14), 2394–2404.
  • Huang, K.C. (2010). Unbiased estimators of mean, variance and sensitivity level for quantitative characteristics in finite population sampling, Metrika, 71(3), 341–352
  • Kadilar, C., & Cingi, H. (2006). Improvement in estimating the population mean in simple random sampling. Applied Mathematics Letters, 19(1), 75–79.
  • Koyuncy, N., & Kadilar, C. (2009). Efficient estimators for the population mean. Hacettepe Journal of Mathematics and Statistics, 38(2), 217–225.
  • Sousa, R., Shabbir, J., Corte Real, P., & Gupta, S. (2010). Ratio estimation of the mean of a sensitive variable in the presence of auxiliary information. Journal of Statistical Theory and Practice, 4(3)495507.
  • Warner, S.L. (1971). The linear randomized response model, Journal of the American Statistical Association, 66(336), 884–888.

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