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A PROFICIENT RANDOMIZED RESPONSE MODEL

Year 2014, Volume: 7 Issue: 3, 87 - 98, 01.09.2014
https://izlik.org/JA89JN92XF

Abstract

In this article, we have suggested a new randomized response model and its properties have beenstudied. The proposed model is found to be more efficient than the randomized response models studiedby Bar – Lev et al. (2004) and Eichhorn and Hayre (1983). The relative efficiency of the proposed modelhas been studied with respect to the Bar – Lev et al.’s (2004) and Eichhorn and Hayre’s (1983) models.Numerical illustrations are also given in support of the present study

References

  • Barabesi, L., Diana, G. and Perri, P.F. (2014). Horvitz-Thompson estimation with randomized response and non-response. Model Assist. Statist. Appl.,9(1), 3-10.
  • Bar –lev, S.K., Bobovitch, E. and Boukai, B.(2004). A note on Randomized response models for quan- titative data. Metrika, 60, 225-250.
  • Eichhorn, B.H. and Hayre, L.S. (1983). Scrambled randomized response methods for obtaining sensitive quantitative data. Jour. Statist. Plann. Infer., 7,307-316.
  • Fox, J.A. and Tracy, P.E. (1986). Randomized Response: A method of Sensitive Surveys. Newbury Park, CA: SEGE Publications.
  • Grewal, I.S., Bansal, M.L., and Sidhu, S.S. (2005–2006). Population mean corresponding to Horvitz– Thompson’s estimator for multi-characteristics using randomized response technique. Model Assist. Statist. Appl. 1, 215-220.
  • Hong, Z. (2005–2006). Estimation of mean in randomized response surveys when answers are incom- pletely truthful. Model Assist. Statist. Appl., 1,221-230.
  • Mahajan, P.K., Sharma, P. and Gupta, R.K. (2007). Optimum stratiŞcation for allocation proportional to strata totals for scrambled response. Model Assist. Statist. Appl., 2(2), 81-88.
  • Odumade, O. and Singh, S. (2009). Improved Bar-Lev, Bobovitch, and Boukai Randomized Response Models. Commun. Statist. Simul. Comput., 38, 473-502.
  • Odumade, O. and Singh, S. (2010). An alternative to the Bar-Lev, Bobovitch, and Boukai Randomized Response Model. Sociol. Meth. Res., 39(2), 206-221.
  • Perri, P.F. (2008). ModiŞed randomized devices for Simmons’ model. Model Assist. Statist. Appl., 3(3), 233-239.
  • Ryu, J.B., Kim, J.M., Heo, T.Y. and Park, C.G. (2005–2006). On stratiŞed randomized response sam- pling. Model Assist. Statist. Appl., 1, 31-36.
  • Singh, S. and Cheng, S.C. (2009). Utilization of higher order moments of scrambling variables in ran- domized response sampling. Jour. Statist. Plann. Infer., 139, 3377-3380.
  • Singh, H. P. and Tarray, T. A. (2012). A StratiŞed Unknown repeated trials in randomized response sampling. Commun. Korean Statist. Soc., 19, (6), 751-759.
  • Singh, H.P. and Tarray, T.A.(2013). A modiŞed survey technique for estimating the proportion and sensitivity in a dichotomous Şnite population. Int. Jour. Adv. Sci. and Tech. Res., 3(6), 459 - 472.
  • Singh, H.P. and Tarray, T.A. (2014). A dexterous randomized response model for estimating a rare sensitive attribute using Poisson distribution. Statist. Prob. Lett., 90,42-45.
  • Warner, S.L.(1965). Randomized response: A survey technique for eliminating evasive answer bias. Jour. Amer. Statist. Assoc.,60,63-69.

Year 2014, Volume: 7 Issue: 3, 87 - 98, 01.09.2014
https://izlik.org/JA89JN92XF

Abstract

References

  • Barabesi, L., Diana, G. and Perri, P.F. (2014). Horvitz-Thompson estimation with randomized response and non-response. Model Assist. Statist. Appl.,9(1), 3-10.
  • Bar –lev, S.K., Bobovitch, E. and Boukai, B.(2004). A note on Randomized response models for quan- titative data. Metrika, 60, 225-250.
  • Eichhorn, B.H. and Hayre, L.S. (1983). Scrambled randomized response methods for obtaining sensitive quantitative data. Jour. Statist. Plann. Infer., 7,307-316.
  • Fox, J.A. and Tracy, P.E. (1986). Randomized Response: A method of Sensitive Surveys. Newbury Park, CA: SEGE Publications.
  • Grewal, I.S., Bansal, M.L., and Sidhu, S.S. (2005–2006). Population mean corresponding to Horvitz– Thompson’s estimator for multi-characteristics using randomized response technique. Model Assist. Statist. Appl. 1, 215-220.
  • Hong, Z. (2005–2006). Estimation of mean in randomized response surveys when answers are incom- pletely truthful. Model Assist. Statist. Appl., 1,221-230.
  • Mahajan, P.K., Sharma, P. and Gupta, R.K. (2007). Optimum stratiŞcation for allocation proportional to strata totals for scrambled response. Model Assist. Statist. Appl., 2(2), 81-88.
  • Odumade, O. and Singh, S. (2009). Improved Bar-Lev, Bobovitch, and Boukai Randomized Response Models. Commun. Statist. Simul. Comput., 38, 473-502.
  • Odumade, O. and Singh, S. (2010). An alternative to the Bar-Lev, Bobovitch, and Boukai Randomized Response Model. Sociol. Meth. Res., 39(2), 206-221.
  • Perri, P.F. (2008). ModiŞed randomized devices for Simmons’ model. Model Assist. Statist. Appl., 3(3), 233-239.
  • Ryu, J.B., Kim, J.M., Heo, T.Y. and Park, C.G. (2005–2006). On stratiŞed randomized response sam- pling. Model Assist. Statist. Appl., 1, 31-36.
  • Singh, S. and Cheng, S.C. (2009). Utilization of higher order moments of scrambling variables in ran- domized response sampling. Jour. Statist. Plann. Infer., 139, 3377-3380.
  • Singh, H. P. and Tarray, T. A. (2012). A StratiŞed Unknown repeated trials in randomized response sampling. Commun. Korean Statist. Soc., 19, (6), 751-759.
  • Singh, H.P. and Tarray, T.A.(2013). A modiŞed survey technique for estimating the proportion and sensitivity in a dichotomous Şnite population. Int. Jour. Adv. Sci. and Tech. Res., 3(6), 459 - 472.
  • Singh, H.P. and Tarray, T.A. (2014). A dexterous randomized response model for estimating a rare sensitive attribute using Poisson distribution. Statist. Prob. Lett., 90,42-45.
  • Warner, S.L.(1965). Randomized response: A survey technique for eliminating evasive answer bias. Jour. Amer. Statist. Assoc.,60,63-69.
There are 16 citations in total.

Details

Other ID JA33AD39VY
Authors

Tanveer A. Tarray This is me

Housila P. Singh. This is me

Publication Date September 1, 2014
IZ https://izlik.org/JA89JN92XF
Published in Issue Year 2014 Volume: 7 Issue: 3

Cite

APA Tarray, T. A., & Singh., H. P. (2014). A PROFICIENT RANDOMIZED RESPONSE MODEL. Istatistik Journal of The Turkish Statistical Association, 7(3), 87-98. https://izlik.org/JA89JN92XF
AMA 1.Tarray TA, Singh. HP. A PROFICIENT RANDOMIZED RESPONSE MODEL. IJTSA. 2014;7(3):87-98. https://izlik.org/JA89JN92XF
Chicago Tarray, Tanveer A., and Housila P. Singh. 2014. “A PROFICIENT RANDOMIZED RESPONSE MODEL”. Istatistik Journal of The Turkish Statistical Association 7 (3): 87-98. https://izlik.org/JA89JN92XF.
EndNote Tarray TA, Singh. HP (September 1, 2014) A PROFICIENT RANDOMIZED RESPONSE MODEL. Istatistik Journal of The Turkish Statistical Association 7 3 87–98.
IEEE [1]T. A. Tarray and H. P. Singh., “A PROFICIENT RANDOMIZED RESPONSE MODEL”, IJTSA, vol. 7, no. 3, pp. 87–98, Sept. 2014, [Online]. Available: https://izlik.org/JA89JN92XF
ISNAD Tarray, Tanveer A. - Singh., Housila P. “A PROFICIENT RANDOMIZED RESPONSE MODEL”. Istatistik Journal of The Turkish Statistical Association 7/3 (September 1, 2014): 87-98. https://izlik.org/JA89JN92XF.
JAMA 1.Tarray TA, Singh. HP. A PROFICIENT RANDOMIZED RESPONSE MODEL. IJTSA. 2014;7:87–98.
MLA Tarray, Tanveer A., and Housila P. Singh. “A PROFICIENT RANDOMIZED RESPONSE MODEL”. Istatistik Journal of The Turkish Statistical Association, vol. 7, no. 3, Sept. 2014, pp. 87-98, https://izlik.org/JA89JN92XF.
Vancouver 1.Tanveer A. Tarray, Housila P. Singh. A PROFICIENT RANDOMIZED RESPONSE MODEL. IJTSA [Internet]. 2014 Sep. 1;7(3):87-98. Available from: https://izlik.org/JA89JN92XF