A varying-coefficient approach to estimating multi-level clustered data models

doi:10.1007/s11749-014-0419-x

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	A varying-coefficient approach to estimating multi-level clustered data models
	You, Jinhong 1; Wan, Alan T. K.2; Liu, Shu 1; Zhou, Yong3
刊名	TEST
	2015-06-01
卷号	24 期号:2 页码:417-440
关键词	Asymptotic normality Correlation Nonparametric Clustered data Two-stage estimation
ISSN号	1133-0686
DOI	10.1007/s11749-014-0419-x
英文摘要	Most of the literature on clustered data models emphasizes two-level clustering, and within-cluster correlation. While multi-level clustered data models can arise in practice, analysis of multi-level clustered data models poses additional difficulties owing to the existence of error correlations both within and across the clusters. It is perhaps for this reason that existing approaches to multi-level clustered data models have been mostly parametric. The purpose of this paper is to develop a varying-coefficient nonparametric approach to the analysis of three-level clustered data models. Because the nonparametric functions are restricted only to some of the variables, this approach has the appeal of avoiding many of the curse of dimensionality problems commonly associated with other nonparametric methods. By applying an undersmoothing technique, taking into account the correlations within and across clusters, we develop an efficient two-stage local polynomial estimation procedure for the unknown coefficient functions. The large and finite sample properties of the resultant estimators are examined; in particular, we show that the resultant estimators are asymptotically normal, and exhibit considerably smaller asymptotic variability than the traditional local polynomial estimators that neglect the correlations within and among clusters. An application example is presented based on a data set extracted from the World Bank's STARS database.
资助项目	City University of Hong Kong[7008134]
WOS研究方向	Mathematics
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000354714100012
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/19784]
专题	应用数学研究所
通讯作者	Wan, Alan T. K.
作者单位	1.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China 2.City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China 3.Chinese Acad Sci, Inst Appl Math, Beijing, Peoples R China
推荐引用方式 GB/T 7714	You, Jinhong,Wan, Alan T. K.,Liu, Shu,et al. A varying-coefficient approach to estimating multi-level clustered data models[J]. TEST,2015,24(2):417-440.
APA	You, Jinhong,Wan, Alan T. K.,Liu, Shu,&Zhou, Yong.(2015).A varying-coefficient approach to estimating multi-level clustered data models.TEST,24(2),417-440.
MLA	You, Jinhong,et al."A varying-coefficient approach to estimating multi-level clustered data models".TEST 24.2(2015):417-440.