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题名

Asymptotic confidence interval construction for proportion ratio based on correlated paired data

作者
发表日期
2019
DOI
发表期刊
ISSN
1054-3406
EISSN
1520-5711
卷号29期号:6页码:1137-1152
摘要
In ophthalmological and otolaryngology studies, measurements obtained from both organs (e.g., eyes or ears) of an individual are often highly correlated. Ignoring the intraclass correlation between paired measurements may yield biased inferences. In this article, four different confidence interval (CI) construction methods (maximum likelihood estimates based Wald-type CI, profile likelihood CI, asymptotic score CI and an existing method adjusted for correlated bilateral data) are applied to this type of correlated bilateral data to construct CI for proportion ratio, taking the intraclass correlation into consideration. The coverage probabilities and widths of the resulting CIs are compared with each other in a Monte Carlo simulation study to evaluate their performances. A real dataset from an ophthalmologic study is used to illustrate our methodology.
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相关链接[Scopus记录]
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语种
英语
学校署名
其他
WOS研究方向
Pharmacology & Pharmacy ; Mathematics
WOS类目
Pharmacology & Pharmacy ; Statistics & Probability
WOS记录号
WOS:000531814500013
出版者
Scopus记录号
2-s2.0-85062470855
来源库
Scopus
引用统计
被引频次[WOS]:4
成果类型期刊论文
条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/44141
专题理学院_数学系
作者单位
1.Department of BiostatisticsUniversity at Buffalo,Buffalo,United States
2.Department of MathematicsSouthern University of Science and Technology,Shenzhen,China
推荐引用方式
GB/T 7714
Peng,Xuan,Liu,Chang,Liu,Song,et al. Asymptotic confidence interval construction for proportion ratio based on correlated paired data[J]. Journal of Biopharmaceutical Statistics,2019,29(6):1137-1152.
APA
Peng,Xuan,Liu,Chang,Liu,Song,&Ma,Chang Xing.(2019).Asymptotic confidence interval construction for proportion ratio based on correlated paired data.Journal of Biopharmaceutical Statistics,29(6),1137-1152.
MLA
Peng,Xuan,et al."Asymptotic confidence interval construction for proportion ratio based on correlated paired data".Journal of Biopharmaceutical Statistics 29.6(2019):1137-1152.
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