A frailty model approach for regression analysis of multivariate current status data

淡江大學機構典藏 > 商管學院 > 統計學系暨研究所 > 期刊論文 > Item 987654321/50445

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題名:	A frailty model approach for regression analysis of multivariate current status data
作者:	Chen, Man-hua;Tong, Xingwei;Sun, Jianguo
貢獻者:	淡江大學統計學系
關鍵詞:	EM algorithm;frailty model;interval censoring;maximum likelihood estimate;multivariate failure time data
日期:	2009
上傳時間:	2010-08-09 17:28:42 (UTC+8)
出版者:	Chichester: John Wiley & Sons Ltd.
摘要:	This paper discusses regression analysis of multivariate current status failure time data (The Statistical Analysis of Interval-censoring Failure Time Data. Springer: New York, 2006), which occur quite often in, for example, tumorigenicity experiments and epidemiologic investigations of the natural history of a disease. For the problem, several marginal approaches have been proposed that model each failure time of interest individually (Biometrics 2000; 56:940-943; Statist. Med. 2002; 21:3715-3726). In this paper, we present a full likelihood approach based on the proportional hazards frailty model. For estimation, an Expectation Maximization (EM) algorithm is developed and simulation studies suggest that the presented approach performs well for practical situations. The approach is applied to a set of bivariate current status data arising from a tumorigenicity experiment.
關聯:	Statistics in Medicine 28(27), pp.3424-3436
DOI:	10.1002/sim.3715
顯示於類別:	[統計學系暨研究所] 期刊論文

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