Mediation Analysis for Censored Survival Data Under an Accelerated Failure Time Model
Mediation Analysis for Censored Survival Data Under an Accelerated Failure Time Model
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DOI：
10.1097/ede.0000000000000687
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发表时间：
2017-09-01
期刊：
影响因子：
5.4
通讯作者：
Williams, Paige L.
中科院分区：
文献类型：
--
作者：
Fulcher, Isabel R.;Tchetgen, Eric J. Tchetgen;Williams, Paige L.
因果中介分析的最新进展已经正式确定了在各种情况下估计直接和间接影响的条件。这些方法已扩展到许多生存结果模型，包括加速失效时间模型，这些模型因其直观的解释而广泛用于广泛的健康应用。在这种情况下，有人建议，在标准假设下，“差异”和“产品”的方法产生等效的暴露对生存结果的间接影响的估计。我们正式表明，这两种方法可能会产生很大的不同的估计存在删失或截断，由于一种形式的模型误设定。具体来说，我们建立，而产品的方法仍然有效的标准假设下，在存在独立的删失，差异的方法可以是有偏见的，在存在这样的删失时，误差分布的加速失效时间模型未能崩溃边缘化的调解人。对于大多数中介变量和结果误差分布的选择，情况总是如此。一个值得注意的例外出现在正常中介正常结果的情况下，我们在存在独立删失的情况下显示差异和乘积估计的一致性。这些结果在模拟研究和两个数据应用中得到了证实。
Recent advances in causal mediation analysis have formalized conditions for estimating direct and indirect effects in various contexts. These approaches have been extended to a number of models for survival outcomes including accelerated failure time models, which are widely used in a broad range of health applications given their intuitive interpretation. In this setting, it has been suggested that under standard assumptions, the "difference" and "product" methods produce equivalent estimates of the indirect effect of exposure on the survival outcome. We formally show that these two methods may produce substantially different estimates in the presence of censoring or truncation, due to a form of model misspecification. Specifically, we establish that while the product method remains valid under standard assumptions in the presence of independent censoring, the difference method can be biased in the presence of such censoring whenever the error distribution of the accelerated failure time model fails to be collapsible upon marginalizing over the mediator. This will invariably be the case for most choices of mediator and outcome error distributions. A notable exception arises in case of normal mediator-normal outcome where we show consistency of both difference and product estimators in the presence of independent censoring. These results are confirmed in simulation studies and two data applications.