Sjölander Arvid, Humphreys Keith, Vansteelandt Stijn, Bellocco Rino, Palmgren Juni
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Biometrics. 2009 Jun;65(2):514-20. doi: 10.1111/j.1541-0420.2008.01108.x.
In many studies, the aim is to learn about the direct exposure effect, that is, the effect not mediated through an intermediate variable. For example, in circulation disease studies it may be of interest to assess whether a suitable level of physical activity can prevent disease, even if it fails to prevent obesity. It is well known that stratification on the intermediate may introduce a so-called posttreatment selection bias. To handle this problem, we use the framework of principal stratification (Frangakis and Rubin, 2002, Biometrics 58, 21-29) to define a causally relevant estimand--the principal stratum direct effect (PSDE). The PSDE is not identified in our setting. We propose a method of sensitivity analysis that yields a range of plausible values for the causal estimand. We compare our work to similar methods proposed in the literature for handling the related problem of "truncation by death."
在许多研究中,目标是了解直接暴露效应,即不通过中间变量介导的效应。例如,在循环系统疾病研究中,评估适当水平的体育活动是否能预防疾病可能是有意义的,即使它未能预防肥胖。众所周知,按中间变量进行分层可能会引入所谓的治疗后选择偏倚。为解决这个问题,我们使用主分层框架(弗兰加基斯和鲁宾,2002年,《生物统计学》58卷,21 - 29页)来定义一个因果相关的估计量——主层直接效应(PSDE)。在我们的设定中,PSDE是无法识别的。我们提出一种敏感性分析方法,该方法能为因果估计量产生一系列合理的值。我们将我们的工作与文献中为处理“因死亡而截断”的相关问题而提出的类似方法进行比较。