A Stratified Hybrid Tripartite Randomized Response Technique

Year 2018, Volume: 31 Issue: 4, 1246 - 1266, 01.12.2018

Olusegun S. Ewemooje , Femi B. Adebola Adedamola A. Adedıran

Abstract

This paper proposes a
new stratified technique to address the problem involving estimation of the
population proportion of people with sensitive attribute(s). Studying the
proposed technique under proportional and Neyman allocations shows that the
proposed technique is more
efficient than (outperforms) the Singh & Gorey [1] and Tarray & Singh
[2] stratified randomized response models. Applying the proposed technique to a
survey on drug use disorder also shows the applicability of the model.

Keywords

Proportional allocation, Neyman allocation, Sensitive attribute, Stratification relative, Efficiency

References

• Adebola F.B. and Adepetun A.O. (2011): A new Tripartite Randomized Response Technique. Journal of the Nigerian Association of Mathematical Physics, 19: 119-122.
• Adebola F.B., Johnson O.O. and Adegoke N.A. (2014): A Modified Stratified Randomized Response Technique. Journal of Mathematics Theory and Modelling. 4(13): 29-42
• Adebola, F. B., Adediran, A. A., & Ewemooje, O. S. (2017). Hybrid tripartite randomized response technique. Communications in Statistics-Theory and Methods, DOI:10.1080/03610926.2016.1277760
• Chaudhuri A. (2001): Estimating sensitive proportions from unequal probability sample using randomized responses. Pakistan Journal of Statistics 17(3): 259–270.
• Ewemooje O. S., Amahia G. N. and Adebola F.B. (2018): Estimating prevalence of induced abortion and multiple sexual partners using improved randomized response technique for two sensitive attributes, Communications in Statistics: Case Studies, Data Analysis and Applications, 3:1-2, 21-28, DOI: 10.1080/23737484.2017.1398057
• Ewemooje O. S. and Amahia G. N. (2016): Improving the Efficiency of Randomized Response Technique for Two Sensitive Characters. FUTA Journal of Research in Sciences, 12 (1): 65 - 72.
• Ewemooje O.S. (2017): Estimating two sensitive characters with equal probabilities of protection, Cogent Mathematics (2017), 4: 1319607. https://doi.org/10.1080/23311835.2017.1319607
• Ewemooje Olusegun S. and Amahia Godwin N. (2015): Improved Randomized Response Technique for Two Sensitive Attributes. Afrika Statistika, 10 (2), 839-852. DOI: 10.16929/as/2015.639.78
• Greenberg, B., Abul-Ela, A; Simmons, W. and Horvitz, D. (1969): The Unrelated question Randomized Response Model: Thereotical framework. Journal of American Statistical Association, 64, 529-539.
• Hong, K., Yum, J. and Lee, H., 1994: A stratified randomized response technique. Korean Journal of Applied Statistics, 7:141–147.
• Kim J.M. and Elam M.E. (2007): A stratified unrelated randomized response model, Statistical Papers 48: 215-233.
• Kim J-M and Warde W.D. (2004): A stratified Warner's randomized response model: Journal of Statistical Planning and Inference 120 (1-2), 155-165
• Mangat, N. S. (1994): An improved randomized response strategy. Journal of Royal Statistical Society, Series B, 56, 93 - 95.
• Mangat, N.S., Singh, S. and Singh, R., (1995): On use of modified randomization device in Warner’s Model. Journal of Indian Society of Operation Research, 14:1-4.
• Singh H. P. and Gorey S. M. (2017): An efficient stratified randomized response model, Journal of Statistical Theory and Practice, DOI: 10.1080/15598608.2017.1350607.
• Singh H.P. and Tarray T.A. (2016): A Sinuous Stratified Unrelated Question Randomized Response Model, Communications in Statistics - Theory and Methods, DOI: 10.1080/03610926.2014.960588.
• Warner, S (1965): Randomized response: a survey technique for eliminating evasive answer bias: Journal of the American Statistical Association 60, 63-69.