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.
