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    Title: A flexible model approach for regression analysis of multivariate interval-censored data
    Other Titles: 以隨機效應模型分析區間設限下的多變量存活資料
    Authors: 林坤宏;Lin, Kuen-hung
    Contributors: 淡江大學統計學系碩士班
    陳蔓樺;Chen, Man-hua
    Keywords: EM演算法;脆弱模型;區間設限;最大概似法;多變量失效時間資料;EM algorithm;frailty model;interval censoring;maximum-likelihood estimate;multivariate failure time data
    Date: 2010
    Issue Date: 2010-09-23 16:41:56 (UTC+8)
    Abstract: 過去已經有許多學者,在考慮每一個併發症之間彼此獨立下,對於回歸分析應用在多變量區間設限型的資料上,提出相關的邊際模型進行討論。
    然而這些模型有著無法探討併發症之間相關性的問題,因此近來學者
    For regression analysis of multivariate interval-censored data, several authors proposed some marginal model approaches, which modeled each time of interest individually. For the problem, those models does not allow for inference about the relationship or association between correlated failure times. The frailty model approach has been commonly used in the analysis of multivariate failure time data and it provides a flexible approach for directly modeling the relationship between correlated failure times.

    In the thesis, we present a full likelihood approach based on the proportional hazard frailty model and estimate of regression parameters by Expectation Maximization (EM) algorithm. The method is applied to a set of bivariate interval-censored data arising from an AIDS clinical trial.
    Appears in Collections:[Graduate Institute & Department of Statistics] Thesis

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