Abstract

This article considers the two-sample testing problem of the survival function of the non terminal event time under semi-competing risks data. The empirical likelihood function is constructed for the survival function estimation of the non terminal event time, then maximize it by the PSO (Particle swarm optimization) algorithm to obtain the MLE. For the testing problem, the article develops the empirical likelihood ratio test to compare the two survival curves. From simulation studies, it shows the performance of the proposed approaches is good. Finally, a real data analysis is presented for illustration.

中文翻译：

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半竞争风险数据下基于经验似然比的两样本检验

摘要

本文考虑半竞争风险数据下非终端事件时间生存函数的两样本检验问题。构造经验似然函数用于非终端事件时间的生存函数估计，然后通过PSO（粒子群优化）算法将其最大化以获得MLE。对于检验问题，本文开发了经验似然比检验来比较两条生存曲线。仿真研究表明，所提出方法的性能良好。最后，给出了一个真实的数据分析来说明。