Genetic studies of two related survival outcomes of a pleiotropic gene are commonly encountered but statistical models to analyze them are rarely developed. To analyze sequencing data, we propose mixed effect Cox proportional hazard models by functional regressions to perform gene-based joint association analysis of two survival traits motivated by our ongoing real studies. These models extend fixed effect Cox models of univariate survival traits by incorporating variations and correlation of multivariate survival traits into the models. The associations between genetic variants and two survival traits are tested by likelihood ratio test statistics. Extensive simulation studies suggest that type I error rates are well controlled and power performances are stable. The proposed models are applied to analyze bivariate survival traits of left and right eyes in the age-related macular degeneration progression.

中文翻译：

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基于基因的双变量生存特征分析，通过功能回归应用于眼病

通常会遇到对多效性基因的两个相关生存结果的遗传研究，但很少开发用于分析它们的统计模型。为了分析测序数据，我们通过功能回归提出了混合效应 Cox 比例风险模型，以对我们正在进行的真实研究所激发的两个生存特征进行基于基因的联合关联分析。这些模型通过将多变量生存特征的变异和相关性纳入模型，扩展了单变量生存特征的固定效应 Cox 模型。遗传变异和两个生存特征之间的关联通过似然比检验统计量来检验。广泛的模拟研究表明，I 类错误率得到了很好的控制，并且电源性能稳定。