There is an increasing trend of research in mediation analysis for survival outcomes. Such analyses help researchers to better understand how exposure affects disease outcomes through mediators. However, due to censored observations in survival outcomes, it is not straightforward to extend mediation analysis from linear models to survival outcomes. In this article, we extend a mediation effect size measure based on $R^2$ in linear regression to survival outcomes. Due to multiple definitions of $R^2$ for survival models, we compare and evaluate five $R^2$ measures for mediation analysis. Based on extensive simulations, we recommend two $R^2$ measures with good operating characteristics. We illustrate the utility of the $R^2$-based mediation measures by analyzing the mediation effects of multiple lifestyle risk factors on the relationship between environmental exposures and time to coronary heart disease and all-cause mortality in the Framingham Heart Study.
翻译:有关生存结果的调解分析研究呈上升趋势。这种分析有助于研究人员更好地了解接触如何通过调解人影响疾病结果。然而,由于在生存结果方面的审查观察,将调解分析从线性模型扩大到生存结果并非直截了当的。在本篇文章中,我们根据以线性回归为生存结果的线性回归为根据的调解规模衡量2雷亚尔。由于对生存模型的多重定义为2雷亚尔,我们比较和评价了5个以2雷亚尔为单位的调解分析措施。根据广泛的模拟,我们建议采取两项具有良好操作特点的2雷亚尔措施。我们通过分析多种生活方式风险因素的调解效果对环境接触和时间与冠心病的关系以及弗雷明翰心脏研究中所有原因的死亡的影响,来说明基于$2美元调解措施的效用。