在論文中我們以不可重複發生的事件為討論的對象，介紹離散時間存活模式的架構，並利用離散時間存活模式與連續時間存活模式、離散時間存活模式與多期二元反應變數模式的關係，找出在某些條件之下，模式之間相對應的情形。另外，針對資料的異質性或相關性的問題，我們在模式中加入隨機效應，以捕捉個人的特質，並彌補解釋變數的不足。同時，我們將說明如何運用最大邊際概似估計法估計模式中的參數。

　This thesis is mainly discussing non-repeatable events, describing the structure of Discrete-Time Survival model, and at the same time discovering the corresponding phenomenon among models under certain conditions by taking the knowledge from the relationship between Discrete-Time Survival model and Continuous-Time Survival model, as well as the relationship between Discrete-Time Survival model and Multiple-Period Dichotomous Response model. Moreover, random effects are added to the models in order to capture the individual characteristics and make up for the shortage of explanation variables for the assessment of heterogeneity and correlation. This thesis also explains how to estimate the parameters in the models by taking the approach of Maximum Marginal Likelihood Estimation.

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