Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2019, Cilt: 32 Sayı: 1, 372 - 383, 01.03.2019

Öz

Kaynakça

  • Arcos, A., Rueda, M, D, M., Singh, S. (2015). A Generalized Approach to Randomised Response for Quantitative Variables. Qual Quant. 49:1239–1256. Arnab, R. (2004). Optional Randomized Response Techniques for Complex Survey Designs. Biometrical Journal. 46:114–124.
  • Bhargava, M., Singh, R. (2000). A Modified Randomization Device for Warner’s Model. Statistica. 60:315-321.
  • Chang, H. J., Huang, K. C. (2001). Estimation of Proportion and Sensitivity of a Qualitative Character. Metrika.53:269-280.
  • Chang, H. J., Wang, C. L., Huang, K. C. (2004): Using Randomized Response to Estimate the Proportion and Truthful Reporting Probability in a Dichotomous Finite Population. Journal of Applied Statistics. 31:565-573.
  • Chaudhuri, A., Pal, S. (2008). Estimating Sensitive Proportions from Warner’s Randomized Responses in Alternative Ways Restricting to Only Distinct Units Sampled. Metrika. 68:147–156.
  • Diana, G. Perri, P. F. (2009). Estimating a Sensitive Proportion Through Randomized Response Procedures Based on Auxiliary Information. Statistical Papers. 50(3): 661–672.
  • Eichhron, B. H., Hayre, L. S. (1983). Scrambled Randomized Response Methods for Obtaining Sensitive Quantitative Data. Journal of Statistical Planning and Inference. 7:307–316.
  • Greenberg, B. G., Abul-Ela Abdel-Latif, A., Simmons, W. R., Horvitz, D. G. (1969). The Unrelated Question RR Model: Theoretical Framework. Journal of the American Statistical Association. 64: 52-539.
  • Greenberg, B.O., Kuebler, R. R. Jr., Abernathy, J. R., Horvitz, D. G. (1971). Application of the Randomized Response Technique in Obtaining Quantitative Data. Journal of the American Statistical Association. 66:243-250.
  • Gupta, S. N., Gupta, B. C., Singh, S. (2002). Estimation of Sensitivity Level of Personal Interview Survey Questions. Journal of Statistical Planning and Inference. 100:239–247.
  • Gupta, S. N., Thornton, B., Shabbir, J., Singhal, S. (2006). A Comparison of Multiplicative and Additive Optional RRT Models. Journal of Statistical Theory and Application. 5:226-239.
  • 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., Mehta, S., Shabbir, J., Dass, B. K. (2013). Generalized Scrambling in Quantitative Optional Randomized Response Models. Communications in Statistics - Theory and Methods. 42:22, 4034-4042, DOI:10.1080/03610926.2011.638427
  • Huang, K. C. (2008). Estimation for the Sensitive Characteristic Using Optional Randomized Response Technique. Quality and Quantity. 42:679-686. Himmelfarb, S., Edgell, S. E. (1980). Additive Constant Model: A Randomized Response Technique for Eliminating Evasiveness to Quantitative Response Questions, Psychol. Bull. 87:525–530.
  • Horvitz, D. G., Shah, B. V., Simmons, W. R. (1967). The Unrelated Question Randomized Response Model. Proc. Social. Statist. Sect., ASA. 65-72.
  • Huang, K. C. (2010). Unbiased Estimators of Mean, Variance and Sensitivity Level for Quantitative Characteristics in Finite Population Sampling. Metrika. 71:341–352.
  • Mangat, N. S. (1994). An Improved Randomized Response Strategy. Journal of the Royal Statistical Society Series B. 56: 93-95.
  • Mangat, N. S., Singh, R., Singh, S. (1997). Violation of Respondent’s Privacy in Moor’s Model—Its Rectification Through a Random Group Strategy. Communication in Statistics Theory and Methods. 26:743–754.
  • Pal, S. (2008). Unbiasedly Estimating the Total of a Stigmatizing Variable from Complex Survey on Permitting Options for Direct or Randomized Responses. Statistical Papers. 49: 157–164.
  • Singh, S., Joarder, A. H. (1997). Unknown Repeated Trials in Randomized Response Sampling. Journal of Indian Society of Agricultural Statistics. 50(1): 103-105.
  • Singh, S., Singh, R., Mangat. N. S. (2000). Some Alternative Strategies to Moor’s Model in Randomized Response Sampling- A Survey Technique for Eliminating Evasive Answer Bias. Journal of Statistical Planning and Inference. 83: 243-255.
  • Singh, S., Horn, S., Singh, R., Mangat, N. S. (2003). On the Use of Modified Randomization Device for Estimating the Prevalence of a Sensitive Attribute. Statistics in Transition. 6(4): 515-522.
  • Ryu, J. B., Kim, J. M., Heo, T. Y., Park, C. G. (2006). On Stratified Randomized Response Sampling. Model Assisted Statistics and Application.1:31–36.
  • Warner, S. L. (1965). Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias. Journal of American Statistical Association. 60:63-69.
  • Yan, Z., Wang, j., Lai, J. (2008). An Efficiency and Protection Degree-Based Comparison Among the Quantitative Randomized Response Strategies. Communications in Statistics - Theory and Methods. 38:3, 400-408.

On Generalized Additive Scrambled Response Modeling in Sensitive Surveys

Yıl 2019, Cilt: 32 Sayı: 1, 372 - 383, 01.03.2019

Öz



In this article, we use additive scrambling to estimate
the mean of a sensitive variable. In the proposed scrambling model, taking G
(>1 ) as a positive integer chosen by the interviewer, each respondent is
asked to randomly draw
G values from
a given distribution of scrambling variable and add average of these randomly
drawn values
  to his/her true response on
the sensitive variable. Using repetition of the scrambling experiment, we
propose a relatively more efficient estimator of sensitive mean without
incurring any additional sampling cost. We present a generalization of additive
scrambled response models and show that most of additive scrambling models are
special cases of suggested generalization. Through algebraic and numerical
comparisons, superiority of the proposed methodology is established. 




Kaynakça

  • Arcos, A., Rueda, M, D, M., Singh, S. (2015). A Generalized Approach to Randomised Response for Quantitative Variables. Qual Quant. 49:1239–1256. Arnab, R. (2004). Optional Randomized Response Techniques for Complex Survey Designs. Biometrical Journal. 46:114–124.
  • Bhargava, M., Singh, R. (2000). A Modified Randomization Device for Warner’s Model. Statistica. 60:315-321.
  • Chang, H. J., Huang, K. C. (2001). Estimation of Proportion and Sensitivity of a Qualitative Character. Metrika.53:269-280.
  • Chang, H. J., Wang, C. L., Huang, K. C. (2004): Using Randomized Response to Estimate the Proportion and Truthful Reporting Probability in a Dichotomous Finite Population. Journal of Applied Statistics. 31:565-573.
  • Chaudhuri, A., Pal, S. (2008). Estimating Sensitive Proportions from Warner’s Randomized Responses in Alternative Ways Restricting to Only Distinct Units Sampled. Metrika. 68:147–156.
  • Diana, G. Perri, P. F. (2009). Estimating a Sensitive Proportion Through Randomized Response Procedures Based on Auxiliary Information. Statistical Papers. 50(3): 661–672.
  • Eichhron, B. H., Hayre, L. S. (1983). Scrambled Randomized Response Methods for Obtaining Sensitive Quantitative Data. Journal of Statistical Planning and Inference. 7:307–316.
  • Greenberg, B. G., Abul-Ela Abdel-Latif, A., Simmons, W. R., Horvitz, D. G. (1969). The Unrelated Question RR Model: Theoretical Framework. Journal of the American Statistical Association. 64: 52-539.
  • Greenberg, B.O., Kuebler, R. R. Jr., Abernathy, J. R., Horvitz, D. G. (1971). Application of the Randomized Response Technique in Obtaining Quantitative Data. Journal of the American Statistical Association. 66:243-250.
  • Gupta, S. N., Gupta, B. C., Singh, S. (2002). Estimation of Sensitivity Level of Personal Interview Survey Questions. Journal of Statistical Planning and Inference. 100:239–247.
  • Gupta, S. N., Thornton, B., Shabbir, J., Singhal, S. (2006). A Comparison of Multiplicative and Additive Optional RRT Models. Journal of Statistical Theory and Application. 5:226-239.
  • 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., Mehta, S., Shabbir, J., Dass, B. K. (2013). Generalized Scrambling in Quantitative Optional Randomized Response Models. Communications in Statistics - Theory and Methods. 42:22, 4034-4042, DOI:10.1080/03610926.2011.638427
  • Huang, K. C. (2008). Estimation for the Sensitive Characteristic Using Optional Randomized Response Technique. Quality and Quantity. 42:679-686. Himmelfarb, S., Edgell, S. E. (1980). Additive Constant Model: A Randomized Response Technique for Eliminating Evasiveness to Quantitative Response Questions, Psychol. Bull. 87:525–530.
  • Horvitz, D. G., Shah, B. V., Simmons, W. R. (1967). The Unrelated Question Randomized Response Model. Proc. Social. Statist. Sect., ASA. 65-72.
  • Huang, K. C. (2010). Unbiased Estimators of Mean, Variance and Sensitivity Level for Quantitative Characteristics in Finite Population Sampling. Metrika. 71:341–352.
  • Mangat, N. S. (1994). An Improved Randomized Response Strategy. Journal of the Royal Statistical Society Series B. 56: 93-95.
  • Mangat, N. S., Singh, R., Singh, S. (1997). Violation of Respondent’s Privacy in Moor’s Model—Its Rectification Through a Random Group Strategy. Communication in Statistics Theory and Methods. 26:743–754.
  • Pal, S. (2008). Unbiasedly Estimating the Total of a Stigmatizing Variable from Complex Survey on Permitting Options for Direct or Randomized Responses. Statistical Papers. 49: 157–164.
  • Singh, S., Joarder, A. H. (1997). Unknown Repeated Trials in Randomized Response Sampling. Journal of Indian Society of Agricultural Statistics. 50(1): 103-105.
  • Singh, S., Singh, R., Mangat. N. S. (2000). Some Alternative Strategies to Moor’s Model in Randomized Response Sampling- A Survey Technique for Eliminating Evasive Answer Bias. Journal of Statistical Planning and Inference. 83: 243-255.
  • Singh, S., Horn, S., Singh, R., Mangat, N. S. (2003). On the Use of Modified Randomization Device for Estimating the Prevalence of a Sensitive Attribute. Statistics in Transition. 6(4): 515-522.
  • Ryu, J. B., Kim, J. M., Heo, T. Y., Park, C. G. (2006). On Stratified Randomized Response Sampling. Model Assisted Statistics and Application.1:31–36.
  • Warner, S. L. (1965). Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias. Journal of American Statistical Association. 60:63-69.
  • Yan, Z., Wang, j., Lai, J. (2008). An Efficiency and Protection Degree-Based Comparison Among the Quantitative Randomized Response Strategies. Communications in Statistics - Theory and Methods. 38:3, 400-408.
Toplam 25 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Statistics
Yazarlar

Waqas Arshad Bu kişi benim

Zawar Hussaın

Yayımlanma Tarihi 1 Mart 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 32 Sayı: 1

Kaynak Göster

APA Arshad, W., & Hussaın, Z. (2019). On Generalized Additive Scrambled Response Modeling in Sensitive Surveys. Gazi University Journal of Science, 32(1), 372-383.
AMA Arshad W, Hussaın Z. On Generalized Additive Scrambled Response Modeling in Sensitive Surveys. Gazi University Journal of Science. Mart 2019;32(1):372-383.
Chicago Arshad, Waqas, ve Zawar Hussaın. “On Generalized Additive Scrambled Response Modeling in Sensitive Surveys”. Gazi University Journal of Science 32, sy. 1 (Mart 2019): 372-83.
EndNote Arshad W, Hussaın Z (01 Mart 2019) On Generalized Additive Scrambled Response Modeling in Sensitive Surveys. Gazi University Journal of Science 32 1 372–383.
IEEE W. Arshad ve Z. Hussaın, “On Generalized Additive Scrambled Response Modeling in Sensitive Surveys”, Gazi University Journal of Science, c. 32, sy. 1, ss. 372–383, 2019.
ISNAD Arshad, Waqas - Hussaın, Zawar. “On Generalized Additive Scrambled Response Modeling in Sensitive Surveys”. Gazi University Journal of Science 32/1 (Mart 2019), 372-383.
JAMA Arshad W, Hussaın Z. On Generalized Additive Scrambled Response Modeling in Sensitive Surveys. Gazi University Journal of Science. 2019;32:372–383.
MLA Arshad, Waqas ve Zawar Hussaın. “On Generalized Additive Scrambled Response Modeling in Sensitive Surveys”. Gazi University Journal of Science, c. 32, sy. 1, 2019, ss. 372-83.
Vancouver Arshad W, Hussaın Z. On Generalized Additive Scrambled Response Modeling in Sensitive Surveys. Gazi University Journal of Science. 2019;32(1):372-83.