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Empirical likelihood inference for general transformation models with right censored data

机译:具有右删失数据的一般转换模型的经验似然推断

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摘要

In this work, we consider empirical likelihood inference for general transformation models with right censored data. The models are a class of flexible semiparametric survival models and include many popular survival models as their special cases. Based on the marginal likelihood function, we define an empirical likelihood ratio statistic. Under some regularity conditions, we show that the empirical likelihood ratio statistic asymptotically follows a standard chi-squared distribution. Through some simulation studies and a real data application, we show that our proposed procedure can work fairly well even for relatively small sample size and high censoring.
机译:在这项工作中,我们考虑具有正确删失数据的一般转换模型的经验似然推断。这些模型是一类灵活的半参数生存模型,并包括许多流行的生存模型作为特例。基于边际似然函数,我们定义了经验似然比统计量。在某些规律性条件下,我们表明经验似然比统计量渐近遵循标准卡方分布。通过一些模拟研究和真实的数据应用,我们证明了即使对于较小的样本量和较高的审查,我们提出的程序也可以很好地工作。

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