Statistical analysis of high-dimensional data has been attracting more and more attention due to the abundance of such data in various fields such as genetic studies or genomics and the existence of many interesting topics. Among them, one is the identification of a gene or genes that have significant effects on the occurrence of or are significantly related to a certain disease. In this paper, we will discuss such a problem that can be formulated as a group test or testing a group of variables or coefficients when one faces right-censored failure time response variable. For the problem, we develop a corrected variance reduced partial profiling (CVRPP) linear regression model and a likelihood ratio test procedure when the failure time of interest follows the additive hazards model. The numerical study suggests that the proposed method works well in practical situations and gives better performance than the existing one. An illustrative example is provided.

中文翻译：

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使用附加危害模型对高维故障时间数据进行分组测试。

由于在诸如遗传研究或基因组学等各个领域中大量此类数据，并且存在许多有趣的主题，因此对高维数据的统计分析已引起越来越多的关注。其中，一种是鉴定对某种疾病的发生具有重大影响或与之显着相关的一个或多个基因。在本文中，我们将讨论这样一个问题，当一个人面对右删失的故障时间响应变量时，该问题可以表述为一组检验或检验一组变量或系数。针对该问题，当关注的故障时间遵循加法危害模型时，我们开发了校正的方差缩减部分轮廓分析（CVRPP）线性回归模型和似然比测试程序。数值研究表明，所提出的方法在实际情况下效果很好，并且比现有方法具有更好的性能。提供了说明性示例。