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DOI: 10.1371/journal.pone.0148267
论文题名:
Parameter Estimation in Stratified Cluster Sampling under Randomized Response Models for Sensitive Question Survey
作者: Xiangke Pu; Ge Gao; Yubo Fan; Mian Wang
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2016
发表日期: 2016-2-17
卷: 11, 期:2
语种: 英语
英文关键词: Graduates ; Undergraduates ; Surveys ; Survey methods ; Lakes ; Research validity ; Normal distribution ; Confidence intervals
英文摘要: Randomized response is a research method to get accurate answers to sensitive questions in structured sample survey. Simple random sampling is widely used in surveys of sensitive questions but hard to apply on large targeted populations. On the other side, more sophisticated sampling regimes and corresponding formulas are seldom employed to sensitive question surveys. In this work, we developed a series of formulas for parameter estimation in cluster sampling and stratified cluster sampling under two kinds of randomized response models by using classic sampling theories and total probability formulas. The performances of the sampling methods and formulas in the survey of premarital sex and cheating on exams at Soochow University were also provided. The reliability of the survey methods and formulas for sensitive question survey was found to be high.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0148267&type=printable
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/25432
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: Institute of Hepatology, Changzhou Third People’s Hospital, Changzhou, Jiangsu Province, 213001, P.R. China;School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu Province, 215123, P.R. China;School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu Province, 215123, P.R. China;School of Public Health, Central South University, Changsha, Hunan Province, 410078, P.R. China

Recommended Citation:
Xiangke Pu,Ge Gao,Yubo Fan,et al. Parameter Estimation in Stratified Cluster Sampling under Randomized Response Models for Sensitive Question Survey[J]. PLOS ONE,2016-01-01,11(2)
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