Western Psychiatric Institute and Clinic, 3811 O’Hara Street, Pittsburgh, PA 15213, USA.
Am J Epidemiol. 2011 Sep 15;174(6):710-7. doi: 10.1093/aje/kwr173. Epub 2011 Jun 7.
Several investigators have demonstrated that the assessment of indirect and direct effects is biased in the presence of a cause that is common to both the mediator and the outcome if one has not controlled for this variable in the analysis. However, little work has been done to quantify the bias caused by this type of unmeasured confounding and determine whether this bias will materially affect conclusions regarding mediation. The author developed a sensitivity analysis program to address this crucial issue. Data from 2 well-known studies in the methodological literature on mediation were reanalyzed using this program. The results of mediation analyses were found not to be as vulnerable to the impact of confounding as previously described; however, these findings varied sharply between the 2 studies. Although the indirect effect observed in one study could potentially be due to a cause common to both the mediator and the outcome, such confounding could not feasibly explain the results of the other study. These disparate results demonstrate the utility of the current sensitivity analysis when assessing mediation.
几位研究人员已经证明，如果在分析中没有控制变量，则在存在同时影响中介变量和结果的共同原因时，间接和直接效应的评估会存在偏差。然而，对于这种未被测量的混杂所引起的偏差的量化工作做得很少，也无法确定这种偏差是否会对关于中介效应的结论产生实质性影响。作者开发了一个敏感性分析程序来解决这个关键问题。使用该程序重新分析了方法学文献中关于中介的两个著名研究的数据。结果发现，中介分析的结果并不像以前描述的那样容易受到混杂的影响；然而，这两种研究的结果差异很大。尽管一项研究中观察到的间接效应可能是由于同时影响中介变量和结果的共同原因，但这种混杂不太可能解释另一项研究的结果。这些不同的结果表明，当前的敏感性分析在评估中介时是有用的。
