A nonparametric analysis of discrete time competing risks data: a comparison of the cause-specific-hazards approach and the vertical approach

Q4 Mathematics
Bonginkosi D. Ndlovu, S. Melesse, T. Zewotir
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引用次数: 0

Abstract

icolaie et al. (2010) have advanced a vertical model as the latest continuous time competing risks model. The main objective of this article is to re-cast this model as a nonparametric model for analysis of discrete time competing risks data. Davis and Lawrance (1989) have advanced a cause-specific-hazard driven method for summarizing discrete time data nonparametrically. The secondary objective of this article is to compare the proposed model to this model. We pay particular attention to the estimates for the cause-specific-hazards and the cumulative incidence functions as well as their respective standard errors.
离散时间竞争风险数据的非参数分析:特定原因风险方法与垂直方法的比较
icolaie等人(2010)提出了一个垂直模型作为最新的连续时间竞争风险模型。本文的主要目的是将该模型重新塑造为一个非参数模型,用于分析离散时间竞争风险数据。Davis和Lawrance(1989)提出了一种基于特定原因的危险驱动方法,用于非框架地总结离散时间数据。本文的次要目的是将所提出的模型与此模型进行比较。我们特别关注特定原因危害的估计值、累积发生率函数及其各自的标准误差。
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来源期刊
Statistics in Transition
Statistics in Transition Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.00
自引率
0.00%
发文量
0
审稿时长
9 weeks
期刊介绍: Statistics in Transition (SiT) is an international journal published jointly by the Polish Statistical Association (PTS) and the Central Statistical Office of Poland (CSO/GUS), which sponsors this publication. Launched in 1993, it was issued twice a year until 2006; since then it appears - under a slightly changed title, Statistics in Transition new series - three times a year; and after 2013 as a regular quarterly journal." The journal provides a forum for exchange of ideas and experience amongst members of international community of statisticians, data producers and users, including researchers, teachers, policy makers and the general public. Its initially dominating focus on statistical issues pertinent to transition from centrally planned to a market-oriented economy has gradually been extended to embracing statistical problems related to development and modernization of the system of public (official) statistics, in general.
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