以隨機效應模型分析區間設限下的多變量存活資料

A flexible model approach for regression analysis of multivariate interval-censored data

林坤宏(Kuen-Hung Lin)

指導教授 ： 陳蔓樺

淡江大學/管理學院/統計學系碩士班/碩士(2010年)

https://doi.org/10.6846/TKU.2010.01057

摘要

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

關鍵字

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

並列摘要

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.

並列關鍵字

EM algorithm ； frailty model ； interval censoring ； maximum-likelihood estimate ； multivariate failure time data

參考文獻

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gression analysis of multivariate current status data. Statistics in Medicine,

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