Almirall Daniel, Griffin Beth Ann, McCaffrey Daniel F, Ramchand Rajeev, Yuen Robert A, Murphy Susan A
Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, U.S.A.
Stat Med. 2014 Sep 10;33(20):3466-87. doi: 10.1002/sim.5892. Epub 2013 Jul 19.
This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal effects of interest in a conditional mean model for a continuous response given time-varying treatments and moderators. We present an easy-to-use estimator of the SNMM that combines an existing regression-with-residuals (RR) approach with an inverse-probability-of-treatment weighting (IPTW) strategy. The RR approach has been shown to identify the moderated time-varying causal effects if the time-varying moderators are also the sole time-varying confounders. The proposed IPTW+RR approach provides estimators of the moderated time-varying causal effects in the SNMM in the presence of an additional, auxiliary set of known and measured time-varying confounders. We use a small simulation experiment to compare IPTW+RR versus the traditional regression approach and to compare small and large sample properties of asymptotic versus bootstrap estimators of the standard errors for the IPTW+RR approach. This article clarifies the distinction between time-varying moderators and time-varying confounders. We illustrate the methodology in a case study to assess if time-varying substance use moderates treatment effects on future substance use.
本文探讨了利用观察性纵向数据研究随时间变化的因果效应调节问题，其中治疗、候选调节变量和可能的混杂因素均随时间变化。结构嵌套均值模型（SNMM）用于在给定随时间变化的治疗和调节变量的条件均值模型中指定感兴趣的调节后的随时间变化的因果效应。我们提出了一种易于使用的SNMM估计器，它将现有的残差回归（RR）方法与逆概率治疗加权（IPTW）策略相结合。如果随时间变化的调节变量也是唯一随时间变化的混杂因素，RR方法已被证明可以识别调节后的随时间变化的因果效应。所提出的IPTW+RR方法在存在一组额外的已知且可测量的随时间变化的混杂因素的情况下，提供了SNMM中调节后的随时间变化的因果效应的估计器。我们使用一个小型模拟实验来比较IPTW+RR与传统回归方法，并比较IPTW+RR方法的渐近标准误差估计器与自助法标准误差估计器的小样本和大样本性质。本文阐明了随时间变化的调节变量和随时间变化的混杂因素之间的区别。我们在一个案例研究中展示了该方法，以评估随时间变化的物质使用是否调节了对未来物质使用的治疗效果。
