English  |  正體中文  |  简体中文  |  Items with full text/Total items : 51921/87065 (60%)
Visitors : 8474108      Online Users : 168
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/87445

    Title: 現狀數據在比例勝算比治癒模型下之分析
    Other Titles: Analysis of current status data under proportional odds cure model
    Authors: 劉慶鴻;Liu, Ching-Hung
    Contributors: 淡江大學數學學系碩士班
    Keywords: 白內障;現狀數據;比例勝算比治癒模型;Cataract;Current Status Data;Proportional odds cure model
    Date: 2012
    Issue Date: 2013-04-13 11:06:45 (UTC+8)
    Abstract: 具有治癒子群的存活資料在右設限資料上已經被廣泛地研究,但較少對於現狀數據的研究。 我們的研究動機來自於一個關於白內障資料的橫斷面研究,其中白內障的發生是現狀設限的,且似乎有一個比例的研究對象似乎不會罹患白內障。 我們利用最大概似法分析具有治癒子群的現狀數據。 一些基於具有治癒子群之現狀數據的迴歸方法已被建立 (Kuk and Chen (1992); Tsodikov (2003); Lu and Ying (2004)),但皆是在混合型治癒模型 (Berkson and Gage (1952)) 之下。 相對的,我們考慮比例勝算比治癒模型 (Zeng et al. (2006)),屬於非混合治癒模型。 為了確保模型參數的可辨識性,我們假設所有右設限觀測者中設限時間最大的研究對象為治癒。 我們進行模擬試驗及白內障資料的分析來評估我們所提出的統計方法。
    Survival data with a cured subgroup have been extensively studied in the context of right-censored data but less for current status data. Motivated by the cataract dataset from a cross-sectional study, where the occurrences of cataract was current status censored and a fraction of subjects seemed not susceptible to cataract, we describe a maximum likelihood method for analyzing current status data with a cured subgroup. Some regression approaches based on current status data with a cured subgroup have been developed, Kuk and Chen (1992); Tsodikov (2003); Lu and Ying (2004), but all under two-component mixture cure models (Berkson and Gage (1952)). Alternatively, we consider the proportional odds cure model (Zeng et al (2006)), a non-mixture model, in this study. To ensure identifiability of the model, in the estimation, we assume the study unit who has the largest censoring time among all right censored observations is cured. We evaluate the proposed method through simulation studies and illustrate it with the cataract data.
    Appears in Collections:[數學學系暨研究所] 學位論文

    Files in This Item:

    File SizeFormat

    All items in 機構典藏 are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback