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研究生： 呂美君
Mei-chun Lu
論文名稱： 第一類區間設限資料之探討
指導教授： 張德新
Der-Shin Chang
口試委員:
學位類別： 碩士
Master
系所名稱： 理學院 - 統計學研究所
Institute of Statistics
論文出版年： 2001
畢業學年度： 89
語文別： 中文
論文頁數： 48
中文關鍵詞： 第一類區間設限資料 、現行狀況資料 、大樣本性質 、線性模式 、廣義加法模式 、比例勝算模式 、Cox PH 模式
外文關鍵詞： case 1 interval censored data, current status data, asympototically normal, linear model, generalized additive model, proportional odds model
相關次數： 點閱：4  下載：0 
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    • 在許多臨床實驗中，無法確知病人的發病或死亡時間，只能知道病人發病或死亡時間在檢測時間之前或之後，記錄檢測時間及發病時間之指標，此類的資料即是所謂的第一類區間設限資料(case 1 interval censored data )。這篇論文便是對近年來有關第一類區間設限資料的文獻所提到在線性模式(linear model)及半參數模式下(semi-parametric model)估計參數的方法及其性質作一整理及探討。

    第一章 緒論...........................................................................................................................1 第二章 線性模式..................................................................................................................3 2.1 估計參數的方法..........................................................................................................4 2.2 大樣本性質.................................................................................................................11 2.3 模擬分析與比較.........................................................................................................16 2.4 推論...............................................................................................................................21 第三章 廣義加法模式.........................................................................................................25 3.1 廣義加法模式下參數之估計及大樣本質..............................................................28 3.2 Huang(1995)建立在比例勝算模式下參數之估計及大樣本性質.......................30 3.3 Rossini & Tsiatis(1996)建立在比例勝算模式下參數之估計及大樣本性質.......32 3.4 Huang(1996)建立在Cox PH 模式下參數之估計及大樣本性質............................34 3.5 Shibosiki(1998)論文之模擬分析與比較....................................................................37 第四章 例子............................................................................................................................41 4.1 腫瘤的發生....................................................................................................................41 4.2 HIV病毒的感染.............................................................................................................45 第五章 結論.............................................................................................................................46

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    Shiboski, S. C. and Jewell, N. P. (1992). Statistic analysis of the time dependence of HIV infectivity based on partner study data. Journal of American Statistic Associate, 87, 360-372.
    Shiboski, S. C. (1998). Generalized additive models for current status data. Lifetime Data Analysis, 4, 29-50.
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