A Stratified Hybrid Tripartite Randomized Response Technique

被引：0

作者：

Ewemooje, Olusegun S. ^{[1
]}

Adebola, Femi B. ^{[1
]}

Adediran, Adedamola A. ^{[1
]}

机构：

[1] Fed Univ Technol Akure, Dept Stat, Akure, Nigeria

来源：

GAZI UNIVERSITY JOURNAL OF SCIENCE | 2018年 / 31卷 / 04期

关键词：

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

D O I：

暂无

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页码：1246 / 1266

页数：21

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