M-estimators based on inverse probability weighted estimating equations with response missing at random

doi:10.1080/03610920601076917

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	M-estimators based on inverse probability weighted estimating equations with response missing at random
	Wang, Qihua
	2007
发表期刊	COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
ISSN	0361-0926
卷号	36 期号:6 页码:1091-1103
摘要	Asymptotic properties of M-estimators with complete data are investigated extensively. In the presence of missing data, however, the standard inference procedures for complete data cannot be applied directly. In this article, the inverse probability weighted method is applied to missing response problem to de. ne M-estimators. The existence of M-estimators is established under very general regularity conditions. Consistency and asymptotic normality of the M-estimators are proved, respectively. An iterative algorithm is applied to calculating the M-estimators. It is shown that one step iteration sufaces and the resulting one-step M-estimate has the same limit distribution as in the fully iterated M-estimators.
关键词	imputation inverse probability weight missing data
DOI	10.1080/03610920601076917
语种	英语
WOS研究方向	Mathematics
WOS类目	Statistics & Probability
WOS记录号	WOS:000247065600004
出版者	TAYLOR & FRANCIS INC
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/5159
专题	应用数学研究所
通讯作者	Wang, Qihua
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China 2.Univ Hong Kong, Dept Stat & Actuarial Sci, Pokfulam, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	Wang, Qihua. M-estimators based on inverse probability weighted estimating equations with response missing at random[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS,2007,36(6):1091-1103.
APA	Wang, Qihua.(2007).M-estimators based on inverse probability weighted estimating equations with response missing at random.COMMUNICATIONS IN STATISTICS-THEORY AND METHODS,36(6),1091-1103.
MLA	Wang, Qihua."M-estimators based on inverse probability weighted estimating equations with response missing at random".COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 36.6(2007):1091-1103.