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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/92546


    Title: Analysis of Multivariate Interval Censoring by Diabetic Retinopathy Study
    Authors: Chen, Man-Hua;Chen, Li-Ching;Lin, Kuen-Hung;Tong, Xingwei
    Contributors: 淡江大學統計學系
    Keywords: EM algorithm;Frailty models;Interval-censoring;Multivariate failure time data
    Date: 2014
    Issue Date: 2013-10-18 09:36:03 (UTC+8)
    Publisher: Philadelphia: Taylor & Francis Inc.
    Abstract: Multivariate failure time data are commonly encountered in biomedical research since each study subject may experience multiple events or because there exists clustering of subjects such that failure times within the same cluster are correlated. There are numerous statistical methods reported for the analysis of right-censored multivariate failure time data and among these. In this paper we use the frailty approach to catch the related survival variables and assume each event is a discrete analogue as an interval of clinical examinations periodically. For estimation, an Expectation Maximization (EM) algorithm is developed and is applied to the diabetic retinopathy study (DRS).
    Relation: Communications in Statistics - Simulation and Computation 43(7), pp.1825-1835
    DOI: 10.1080/03610918.2012.745557
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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