A pseudolikelihood method for analyzing interval censored data
A pseudolikelihood method for analyzing interval censored data
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DOI：
10.1093/biomet/asm011
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发表时间：
2007-03-01
期刊：
影响因子：
2.7
通讯作者：
Banerjee, Moulinath
中科院分区：
文献类型：
--
作者：
Sen, Bodhisattva;Banerjee, Moulinath
本文提出了一种基于伪概率比的方法，用于估计混合区间删失模型中生存时间的分布函数。在混合案例模型中，一个人被观察了随机的次数，每次都记录下一个事件是否发生。人们试图估计事件发生的时间分布。我们使用泊松过程的似然函数的基础上，构建一个pseudolikadratio统计测试值的分布函数在一个固定的点，并表明，这收敛于零假设下的一个已知的极限分布，可以表示为一个功能的不同的凸次项的双边布朗运动过程的抛物线漂移。然后通过标准反演进行置信集的构造。置信集的计算很简单，需要使用池相邻违规者算法或标准保序回归算法。我们还说明了所提出的方法优于竞争对手的基础上，resstriking技术或最大pseudolikestimate的极限分布，通过模拟研究，并说明了不同的方法在一组血友病患者的数据集，涉及时间HIV血清转换。
We introduce a method based on a pseudolikelihood ratio for estimating the distribution function of the survival time in a mixed-case interval censoring model. In a mixed-case model, an individual is observed a random number of times, and at each time it is recorded whether an event has happened or not. One seeks to estimate the distribution of time to event. We use a Poisson process as the basis of a likelihood function to construct a pseudolikelihood ratio statistic for testing the value of the distribution function at a fixed point, and show that this converges under the null hypothesis to a known limit distribution, that can be expressed as a functional of different convex minorants of a two-sided Brownian motion process with parabolic drift. Construction of confidence sets then proceeds by standard inversion. The computation of the confidence sets is simple, requiring the use of the pool-adjacent-violators algorithm or a standard isotonic regression algorithm. We also illustrate the superiority of the proposed method over competitors based on resampling techniques or on the limit distribution of the maximum pseudolikelihood estimator, through simulation studies, and illustrate the different methods on a dataset involving time to HIV seroconversion in a group of haemophiliacs.