政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/125123
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113648/144635 (79%)
Visitors : 51579366      Online Users : 908
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU 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
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/125123


    Title: Semiparametric regression analysis of recurrent gap times in the presence of competing risks
    Authors: 黃佳慧
    Huang, C.-H.
    Chen, Y.-H.
    Chuang, Y.-W.
    Contributors: 統計系
    Keywords: Competing risks;martingale processes;mixture model;multiple events;recurrent data
    Date: 2017-07
    Issue Date: 2019-08-13 09:18:36 (UTC+8)
    Abstract: When a disease progression goes through several stages marked by a nonterminal, recurrent event such as relapse, or a terminal event such as death, which terminates the progression, researchers can be concerned with the duration or gap times between successive events (stages) and wish to study the covariates effects on the gap times. How previous events or gap times affect the current gap time can be also of interest. We propose a unifying framework for joint regression analysis of gap times between successive events. The proposed mixture modeling framework consists of a logistic regression for predicting the path of transition (to a nonterminal or terminal event) at each stage, and a proportional hazards model for predicting the gap times for transition to the nonterminal and terminal events at each stage; these components of the model are conditional on the past event history and stage-specific covariates. In particular, when the number of stages is fixed at one or two, the proposed framework can be applied to the analysis of convetional competing risks or semicompeting risks data. We develop a semiparametric maximum likelihood inference procedure for the proposed models. For which the large sample theory follows directly from martingale theory. Explicit expressions for the information matrix are derived, which facilitate direct variance estimation and convenient computation. Simulation results reveal the proposal`s worth, and applications to two clinical studies illustrate its utility.
    Relation: Statistica Sinica, Vol.27, pp.1059-1077
    Data Type: article
    Appears in Collections:[Department of Statistics] Periodical Articles

    Files in This Item:

    File SizeFormat
    61.pdf2366KbAdobe PDF2273View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback