Enhanced empirical likelihood estimation of incubation period of COVID-19 by integrating published information

doi:10.1002/sim.9026

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	Enhanced empirical likelihood estimation of incubation period of COVID-19 by integrating published information
	Jiang, Zhongfeng 1; Yang, Baoying 2; Qin, Jing 3; Zhou, Yong 4,5
	2021-05-11
发表期刊	STATISTICS IN MEDICINE
ISSN	0277-6715
页码	17
摘要	Since the outbreak of the new coronavirus disease (COVID-19), a large number of scientific studies and data analysis reports have been published in the International Journal of Medicine and Statistics. Taking the estimation of the incubation period as an example, we propose a low-cost method to integrate external research results and available internal data together. By using empirical likelihood method, we can effectively incorporate summarized information even if it may be derived from a misspecified model. Taking the possible uncertainty in summarized information into account, we augment a logarithm of the normal density in the log empirical likelihood. We show that the augmented log-empirical likelihood can produce enhanced estimates for the underlying parameters compared with the method without utilizing auxiliary information. Moreover, the Wilks' theorem is proved to be true. We illustrate our methodology by analyzing a COVID-19 incubation period data set retrieved from Zhejiang Province and summarized information from a similar study in Shenzhen, China.
关键词	augmented log‐ empirical likelihood COVID‐ 19 incubation period meta‐ analysis Wilks&apos theorem
DOI	10.1002/sim.9026
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[11501472] ; State Key Program of National Natural Science Foundation of China[71931004]
WOS研究方向	Mathematical & Computational Biology ; Public, Environmental & Occupational Health ; Medical Informatics ; Research & Experimental Medicine ; Mathematics
WOS类目	Mathematical & Computational Biology ; Public, Environmental & Occupational Health ; Medical Informatics ; Medicine, Research & Experimental ; Statistics & Probability
WOS记录号	WOS:000649037300001
出版者	WILEY
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/58630
专题	中国科学院数学与系统科学研究院
通讯作者	Yang, Baoying
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 2.Southwest Jiaotong Univ, Dept Stat, Coll Math, Chengdu 611756, Sichuan, Peoples R China 3.NIAID, NIH, 9000 Rockville Pike, Bethesda, MD 20892 USA 4.MOE, Key Lab Adv Theory & Applicat Stat & Data Sci, Shanghai, Peoples R China 5.East China Normal Univ, Acad Stat & Interdisciplinary Sci, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Jiang, Zhongfeng,Yang, Baoying,Qin, Jing,et al. Enhanced empirical likelihood estimation of incubation period of COVID-19 by integrating published information[J]. STATISTICS IN MEDICINE,2021:17.
APA	Jiang, Zhongfeng,Yang, Baoying,Qin, Jing,&Zhou, Yong.(2021).Enhanced empirical likelihood estimation of incubation period of COVID-19 by integrating published information.STATISTICS IN MEDICINE,17.
MLA	Jiang, Zhongfeng,et al."Enhanced empirical likelihood estimation of incubation period of COVID-19 by integrating published information".STATISTICS IN MEDICINE (2021):17.