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	Estimation of linear error-in-covariables models with validation data under random censorship
	Wang, QH
	2000
关键词	linear model validation data random censoring asymptotic normality SURROGATE ENDPOINTS CLINICAL-TRIALS REGRESSION SAMPLE
英文摘要	Consider the linear models of the form Y = X(tau)beta + epsilon with the response Y censored randomly on the right and X measured erroneously. Without specifying any error models, in this paper, a semiparametric method is applied to the estimation of the parametric vector beta with the help of proper validation data. For the proposed estimator, an asymptotic representation is established and the asymptotic normality is also proved. (C) 2000 Academic Press. AMS 1991 subject classifications: primary, 62F05, 62J05; secondary, 62G05, 62E20.; Statistics & Probability; SCI(E); 8; ARTICLE; 2; 245-266; 74
语种	英语
出处	SCI
出版者	多变量分析杂志
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/257756]
专题	数学科学学院
推荐引用方式 GB/T 7714	Wang, QH. Estimation of linear error-in-covariables models with validation data under random censorship. 2000-01-01.

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