本篇論文主要研究為使用半參數模型來描述當復發事件為非獨立區間設限觀測時間(稱為追蹤式計數資料)以及具有測量誤差時，
如何估計模型的共變數的參數。區間設限時間指的是在兩次的實驗觀測時間之間具有事件的發生，但是我們無法得知事件的真實發生時間，
而非獨立區間設限則是指實驗對象的實驗觀測時間與事件本身有關。
復發事件為，在一觀測時間內，一觀測對象，重複發生同一事件(如:腫瘤復發)。
而本文中所使用的資料型態區間設限觀測時間的復發事件又稱為追蹤式計數資料(panel count data)。
本論文處理非獨立區間設限模型的方式與 Huang et al. (2006) 提出方法類似，但我們多加入共變數有測量誤差的情形進行討論，
並且分別使用三種校正方法分別為 : 迴歸校正法 、 模擬外插法 、 分數函數校正法來校正共變數的測量誤差。
使用不同的模擬生成資料來比較校正法在非獨立區間設限以及考慮測量誤差下的結果，分析結果顯示在處理非獨立區間設限問題時，
如果我們忽略測量誤差結果有較大的偏誤，而分數函數校正法的共變數參數估計量偏誤最小，且在不同測量誤差變異下，表現相對穩定，
模擬外插法在誤差變異放大時，會出現嚴重的偏誤情形，而迴歸校正法雖然表現不錯，但偏誤都較分數函數校正法略大。
最後我們利用以上模型來分析膀胱腫瘤復發資料，並考慮腫瘤大小有不同程度測量誤差時的估計結果，
結果發現當測量誤差變大時，各估計量的結果差異越趨明顯，但是皆可看出 Thiotepa 群的腫瘤復發次數較少。

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