Semiparametric regression analysis with missing response at random

doi:10.1198/016214504000000449

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	Semiparametric regression analysis with missing response at random
	Wang, QH; Linton, O ; Hardle, W
	2004-06-01
发表期刊	JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
ISSN	0162-1459
卷号	99 期号:466 页码:334-345
摘要	We develop inference tools in a semiparametric partially linear regression model with missing response data. A class of estimators is defined that includes as special cases a semiparametric regression imputation estimator, a marginal average estimator, and a (marginal) propensity score weighted estimator. We show that any of our class of estimators is asymptotically normal. The three special estimators have the same asymptotic variance. They achieve the serniparametric efficiency bound in the homoscedastic Gaussian case. We show that the jackknife method can be used to consistently estimate the asymptotic variance. Our model and estimators are defined with a view to avoid the curse of dimensionality, which severely limits the applicability of existing methods. The empirical likelihood method is developed. It is shown that when missing responses are imputed using the semiparametric regression method the empirical log-likelihood is asymptotically a scaled chi-squared variable. An adjusted empirical log-likelihood ratio, which is asymptotically standard chisquared, is obtained. Also, a bootstrap empirical log-likelihood ratio is derived and its distribution is used to approximate that of the imputed empirical log-likelihood ratio. A simulation study is conducted to compare the adjusted and bootstrap empirical likelihood with the normal approximation-based method in terms of coverage accuracies and average lengths of confidence intervals. Based on biases and standard errors, a comparison is also made by simulation between the proposed estimators and the related estimators.
关键词	empirical likelihood partially linear model semiparametric imputation weighting estimator
DOI	10.1198/016214504000000449
语种	英语
WOS研究方向	Mathematics
WOS类目	Statistics & Probability
WOS记录号	WOS:000221572500004
出版者	AMER STATISTICAL ASSOC
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/606
专题	应用数学研究所
通讯作者	Wang, QH
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China 2.Univ London London Sch Econ & Polit Sci, Dept Econ, London WC2A 2AE, England 3.Humboldt Univ, Ctr Appl Stat & Econ, D-10178 Berlin, Germany
推荐引用方式 GB/T 7714	Wang, QH,Linton, O,Hardle, W. Semiparametric regression analysis with missing response at random[J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION,2004,99(466):334-345.
APA	Wang, QH,Linton, O,&Hardle, W.(2004).Semiparametric regression analysis with missing response at random.JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION,99(466),334-345.
MLA	Wang, QH,et al."Semiparametric regression analysis with missing response at random".JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 99.466(2004):334-345.