Joint analysis of interval-censored failure time data and panel count data.
Joint analysis of interval-censored failure time data and panel count data.
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区间删失故障时间数据和面板计数数据的联合分析
DOI：
10.1007/s10985-017-9397-0
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发表时间：
2018-01
影响因子：
1.3
通讯作者：
Sun J
中科院分区：
文献类型：
--
作者：
Xu D;Zhao H;Sun J
区间截尾失效时间数据和面板计数数据是事件历史研究中常见的两类不完全数据，已有许多方法分别对它们进行分析(Sun在区间截尾失效时间数据的统计分析中)。施普林格，纽约，2006；孙和赵在面板计数数据的统计分析中。施普林格，纽约，2013)。有时，人们可能对它们的联合分析感兴趣或需要进行它们的联合分析，例如在具有复合终点的临床试验中，对于这些临床试验，文献中似乎没有既定的方法。本文提出了一种用于联合分析的筛选极大似然方法，该方法使用Bernstein多项式来逼近未知函数。建立了所得估计的渐近性质，特别地，所提出的回归参数估计是半参数有效的。此外，还进行了广泛的模拟研究，并将所提出的方法应用于一组来自皮肤癌研究的真实数据。
Interval-censored failure time data and panel count data are two types of incomplete data that commonly occur in event history studies and many methods have been developed for their analysis separately (Sun in The statistical analysis of interval-censored failure time data. Springer, New York, 2006; Sun and Zhao in The statistical analysis of panel count data. Springer, New York, 2013). Sometimes one may be interested in or need to conduct their joint analysis such as in the clinical trials with composite endpoints, for which it does not seem to exist an established approach in the literature. In this paper, a sieve maximum likelihood approach is developed for the joint analysis and in the proposed method, Bernstein polynomials are used to approximate unknown functions. The asymptotic properties of the resulting estimators are established and in particular, the proposed estimators of regression parameters are shown to be semiparametrically efficient. In addition, an extensive simulation study was conducted and the proposed method is applied to a set of real data arising from a skin cancer study.
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影响因子：
4.5
作者：
SHEN, XT;WONG, WH
通讯作者：
WONG, WH
影响因子：
1
作者：
Zhang, Ying;Hua, Lei;Huang, Jian
通讯作者：
Huang, Jian
影响因子：
3.7
作者：
Huang, J;Rossini, AJ
通讯作者：
Rossini, AJ
影响因子：
2.7
作者：
Sen, Bodhisattva;Banerjee, Moulinath
通讯作者：
Banerjee, Moulinath
影响因子：
1.9
作者：
FINKELSTEIN, DM
通讯作者：
FINKELSTEIN, DM