Semiparametric mixed-effects models for clustered doubly censored data

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题名:	Semiparametric mixed-effects models for clustered doubly censored data
作者:	Shen, P.-S.
贡献者:	Department of Statistics, Tunghai University Taichung
关键词:	frailty model;left censoring;semiparametric transformation model
日期:	2012
上传时间:	2013-05-15T09:06:17Z (UTC)
摘要:	The Cox proportional frailty model with a random effect has been proposed for the analysis of right-censored data which consist of a large number of small clusters of correlated failure time observations. For right-censored data, Cai et al. [3] proposed a class of semiparametric mixed-effects models which provides useful alternatives to the Cox model. We demonstrate that the approach of Cai et al. [3] can be used to analyze clustered doubly censored data when both left- and right-censoring variables are always observed. The asymptotic properties of the proposed estimator are derived. A simulation study is conducted to investigate the performance of the proposed estimator. ? 2012 Copyright Taylor and Francis Group, LLC.
關聯:	Journal of Applied Statistics Volume 39, Issue 9, September 2012, Pages 1881-1892
显示于类别:	[統計學系所] 期刊論文

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