We study explained variation under the additive hazards regression model for right‐censored data. We consider different approaches for developing such a measure, and focus on one that estimates the proportion of variation in the failure time explained by the covariates. We study the properties of the measure both analytically, and through extensive simulations. We apply the measure to a well‐known survival dataset as well as the linked surveillance, epidemiology, and end results‐Medicare database for prediction of mortality in early stage prostate cancer patients using high‐dimensional claims codes.

中文翻译：

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附加危害模型下的解释变异

我们在右删失数据的加性危害回归模型下研究了解释的变异。我们考虑开发这种方法的不同方法，并着重于一种估计由协变量解释的故障时间变化的比例的方法。我们通过分析和广泛的模拟研究该度量的属性。我们将该措施应用于知名的生存数据集以及相关的监视，流行病学和最终结果医疗保险数据库，以使用高维索赔代码预测早期前列腺癌患者的死亡率。