南方科技大学知识苑(SUSTech KC): Poisson–Poisson item count techniques for surveys with sensitive discrete quantitative data

题名	Poisson–Poisson item count techniques for surveys with sensitive discrete quantitative data
作者	Liu，Yin 1; Tian，Guo Liang2 ; Wu，Qin 3; Tang，Man Lai 4
发表日期	2019-10-01
DOI	10.1007/s00362-017-0895-7
发表期刊	STATISTICAL PAPERS 影响因子和分区
ISSN	0932-5026
EISSN	1613-9798
卷号	60 期号:5页码:1763-1791
摘要	This paper proposes a new Poisson–Poisson item count technique (ICT), which is an extension of the existing Poisson ICT of Tian et al. (Stat Methods Med Res. doi:10.1177/0962280214563345, 2017) from estimating the proportion associated with a sensitive binary variable to estimating the Poisson mean associated with a sensitive discrete quantitative variable. The Poisson–Poisson ICT can be used to collect and analyze sensitive discrete quantitative data, where an independent non-sensitive Poisson random variable with mean parameter λ is introduced to facilitate the data collection. Specifically, we first propose the single-trial and multiple-trial survey designs for the Poisson–Poisson ICT with known λ and develop the corresponding statistical inference methods. Then, we compare the single-trial design with the multiple-trial design from the viewpoints of relative efficiency and the degree of privacy protection. Furthermore, we propose a new survey design for the Poisson–Poisson ICT with unknown λ. The allocation of sample sizes in two groups is also discussed. Simulation studies are performed to illustrate the proposed methods. In addition, we also consider the regression model based on the Poisson–Poisson ICT with known λ for the single-trial case. Finally, two real surveys on the gift-giving behavior in two different universities are conducted by using the proposed techniques.
关键词	Item count technique Multiple-trial design Randomized response technique Sensitive discrete quantitative data Single-trial design
相关链接	[Scopus记录]
收录类别	SCI ; SSCI
语种	英语
学校署名	其他
资助项目	Research Grant Council of the Hong Kong Special Administrative Region[UGC/FDS14/P01/14] ; Research Grant Council of the Hong Kong Special Administrative Region[UGC/FDS14/P01/16]
WOS研究方向	Mathematics
WOS类目	Statistics & Probability
WOS记录号	WOS:000504900500016
出版者	SPRINGER
ESI学科分类	MATHEMATICS
Scopus记录号	2-s2.0-85016105832
来源库	Scopus
引用统计	被引频次[WOS]：2
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/43865
专题	理学院_数学系
作者单位	1.School of Statistics and MathematicsZhongnan University of Economics and Law,Wuhan,China 2.Department of MathematicsSouthern University of Science and Technology,Shenzhen,China 3.School of Mathematical ScienceSouth China Normal University,Guangzhou,China 4.Department of Mathematics and StatisticsHang Seng Management College,Shatin,Hang Shin Link, Siu Lek Yuen,Hong Kong
推荐引用方式 GB/T 7714	Liu，Yin,Tian，Guo Liang,Wu，Qin,等. Poisson–Poisson item count techniques for surveys with sensitive discrete quantitative data[J]. STATISTICAL PAPERS,2019,60(5):1763-1791.
APA	Liu，Yin,Tian，Guo Liang,Wu，Qin,&Tang，Man Lai.(2019).Poisson–Poisson item count techniques for surveys with sensitive discrete quantitative data.STATISTICAL PAPERS,60(5),1763-1791.
MLA	Liu，Yin,et al."Poisson–Poisson item count techniques for surveys with sensitive discrete quantitative data".STATISTICAL PAPERS 60.5(2019):1763-1791.