BibTex RIS Cite

AN IMPROVED NEW ADDITIVE MODEL

Year 2016, Volume: 29 Issue: 1, 159 - 165, 21.03.2016

Tanveer A. Tarray , Housila P. Singh

Abstract

In this paper, an improved new additive model has been proposed. The proposed model is found to be more efficient than the randomized response models studied by Gjestvang and Singh (2009) and Singh (2010). The relative efficiency of the proposed model has been studied with respect to the Gjestvang and Singh (2009) and Singh (2010) model. It is found that the envisaged model is superior to those additive models earlier considered by Gjestvang and Singh (2009) and Singh (2010) under certain realistic conditions. Numerical illustrations are also given in support of the present study.

Keywords

Randomized response sampling Estimation of proportion sensitive quantitative variable.

References

  • Fox, J.A., Tracy, P. E., “Randomized Response: A method of Sensitive Surveys”, CA: SEGE Publications, (1986). Newbury Park,
  • Gjestvang, C.R., Singh, S., “A new randomized response model”, Jour. Roy. 530, (2006). Statist.Soc., 68,
  • Gjestvang, C. R., Singh, S., “An improved randomized response model: Estimation of mean”, Jour. Appl. Statist., 32 (12), 1361-1367, (2009).
  • Gupta, S., Shabbir, J., Sehra, S., “Mean and Sensitivity Estimation in Optional Randomized Response Model”, Jour. Statist. Plan. Infer. , 140 (10) 2870- , ( 2010).
  • Gupta, S., Shabbir, J., Sousa, S., Corte-Real, P., “Estimation of the Mean of a Sensitive Variable in the Presence of Auxiliary Information”, Comm. Statist. Theo. Meth., 41, 2394- 2404, ( 2012).
  • Singh, H.P., Mathur, N., “Estimation of population mean with known under optional response model using scrambled response 1093, (2004). of variation technique”.Statist. Trans., 6, (7),
  • Singh, H.P., Mathur, N., “Estimation of population mean when coefficient of using scrambled response technique”, Jour. Statist. Plan. (2005). variation is known , 144,
  • Singh, H.P., Tarray, T.A., “A modified survey technique for estimating the sensitivity in a dichotomous finite population”, Inter. Jour. Advanc. Scien. Techn. Res., 3(6), – 472, (2013). proportion and a rare sensitive
  • Tarray, T.A., Singh, H.P., “A Proficient randomized response model”. Istatistika: Statist. Assoc, In Press, (2015). Jour. Turkey
  • Singh, S., “Proposed optimal orthogonal new additive model (POONAM)”, LXX (1), 73-81, (2010). Statistica, anno,
  • Warner, S.L., “Randomized response: A survey technique for eliminating evasive bias”, Jour. Amer. Statist. Assoc., 60, 63-69, (1965). answer

Year 2016, Volume: 29 Issue: 1, 159 - 165, 21.03.2016

Tanveer A. Tarray , Housila P. Singh

Abstract

References

  • Fox, J.A., Tracy, P. E., “Randomized Response: A method of Sensitive Surveys”, CA: SEGE Publications, (1986). Newbury Park,
  • Gjestvang, C.R., Singh, S., “A new randomized response model”, Jour. Roy. 530, (2006). Statist.Soc., 68,
  • Gjestvang, C. R., Singh, S., “An improved randomized response model: Estimation of mean”, Jour. Appl. Statist., 32 (12), 1361-1367, (2009).
  • Gupta, S., Shabbir, J., Sehra, S., “Mean and Sensitivity Estimation in Optional Randomized Response Model”, Jour. Statist. Plan. Infer. , 140 (10) 2870- , ( 2010).
  • Gupta, S., Shabbir, J., Sousa, S., Corte-Real, P., “Estimation of the Mean of a Sensitive Variable in the Presence of Auxiliary Information”, Comm. Statist. Theo. Meth., 41, 2394- 2404, ( 2012).
  • Singh, H.P., Mathur, N., “Estimation of population mean with known under optional response model using scrambled response 1093, (2004). of variation technique”.Statist. Trans., 6, (7),
  • Singh, H.P., Mathur, N., “Estimation of population mean when coefficient of using scrambled response technique”, Jour. Statist. Plan. (2005). variation is known , 144,
  • Singh, H.P., Tarray, T.A., “A modified survey technique for estimating the sensitivity in a dichotomous finite population”, Inter. Jour. Advanc. Scien. Techn. Res., 3(6), – 472, (2013). proportion and a rare sensitive
  • Tarray, T.A., Singh, H.P., “A Proficient randomized response model”. Istatistika: Statist. Assoc, In Press, (2015). Jour. Turkey
  • Singh, S., “Proposed optimal orthogonal new additive model (POONAM)”, LXX (1), 73-81, (2010). Statistica, anno,
  • Warner, S.L., “Randomized response: A survey technique for eliminating evasive bias”, Jour. Amer. Statist. Assoc., 60, 63-69, (1965). answer
There are 11 citations in total.

Details

Journal Section Statistics
Authors

Tanveer A. Tarray

Housila P. Singh This is me

Publication Date March 21, 2016
Published in Issue Year 2016 Volume: 29 Issue: 1

Cite

APA Tarray, T. A., & Singh, H. P. (2016). AN IMPROVED NEW ADDITIVE MODEL. Gazi University Journal of Science, 29(1), 159-165.
AMA Tarray TA, Singh HP. AN IMPROVED NEW ADDITIVE MODEL. Gazi University Journal of Science. March 2016;29(1):159-165.
Chicago Tarray, Tanveer A., and Housila P. Singh. “AN IMPROVED NEW ADDITIVE MODEL”. Gazi University Journal of Science 29, no. 1 (March 2016): 159-65.
EndNote Tarray TA, Singh HP (March 1, 2016) AN IMPROVED NEW ADDITIVE MODEL. Gazi University Journal of Science 29 1 159–165.
IEEE T. A. Tarray and H. P. Singh, “AN IMPROVED NEW ADDITIVE MODEL”, Gazi University Journal of Science, vol. 29, no. 1, pp. 159–165, 2016.
ISNAD Tarray, Tanveer A. - Singh, Housila P. “AN IMPROVED NEW ADDITIVE MODEL”. Gazi University Journal of Science 29/1 (March 2016), 159-165.
JAMA Tarray TA, Singh HP. AN IMPROVED NEW ADDITIVE MODEL. Gazi University Journal of Science. 2016;29:159–165.
MLA Tarray, Tanveer A. and Housila P. Singh. “AN IMPROVED NEW ADDITIVE MODEL”. Gazi University Journal of Science, vol. 29, no. 1, 2016, pp. 159-65.
Vancouver Tarray TA, Singh HP. AN IMPROVED NEW ADDITIVE MODEL. Gazi University Journal of Science. 2016;29(1):159-65.