A class of multi-sample nonparametric tests for panel count data
A class of multi-sample nonparametric tests for panel count data
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DOI：
10.1007/s10463-008-0209-x
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发表时间：
2011-02
影响因子：
1
通讯作者：
Narayanaswamy Balakrishnan;Xingqiu Zhao
中科院分区：
文献类型：
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作者：
Narayanaswamy Balakrishnan;Xingqiu Zhao
本文研究了考虑循环事件时自然出现的点过程均值函数与面板计数数据的多样本非参数比较问题。例如，此类数据经常出现在医学后续研究和可靠性实验中。对于所考虑的问题，我们基于点过程估计的均值函数之间的加权差的积分构造了一类非参数检验统计量。当去除权重过程的单调性假设时，严格推导了所提出统计量的渐近分布，并通过蒙特卡罗模拟检验了它们的有限样本性质。仿真结果表明，该方法具有较好的实用性，比现有的测试方法略强。一组来自癌症研究的面板计数数据被分析并作为一个说明性的例子提出。
This paper considers the problem of multi-sample nonparametric comparison of mean functions of point processes with panel count data, which arise naturally when recurrent events are considered. Such data frequently occur in medical follow-up studies and reliability experiments, for example. For the problem considered, we construct a class of nonparametric test statistics based on the integrated weighted differences between the estimated mean functions of the point processes. The asymptotic distributions of the proposed statistics are rigorously derived when the monotonicity assumptions for weight processes are removed, and their finite-sample properties are examined through Monte Carlo simulations. The simulation results show that the proposed methods are good for practical use and are slightly powerful than the existing tests. A set of panel count data from a cancer study is analyzed and presented as an illustrative example.