Lesko Catherine R, Buchanan Ashley L, Westreich Daniel, Edwards Jessie K, Hudgens Michael G, Cole Stephen R
From the aDepartment of Epidemiology, University of North Carolina, Chapel Hill, NC; bDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; cDepartment of Biostatistics, University of North Carolina, Chapel Hill, NC; and dDepartment of Biostatistics and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
Epidemiology. 2017 Jul;28(4):553-561. doi: 10.1097/EDE.0000000000000664.
Great care is taken in epidemiologic studies to ensure the internal validity of causal effect estimates; however, external validity has received considerably less attention. When the study sample is not a random sample of the target population, the sample average treatment effect, even if internally valid, cannot usually be expected to equal the average treatment effect in the target population. The utility of an effect estimate for planning purposes and decision making will depend on the degree of departure from the true causal effect in the target population due to problems with both internal and external validity. Herein, we review concepts from recent literature on generalizability, one facet of external validity, using the potential outcomes framework. Identification conditions sufficient for external validity closely parallel identification conditions for internal validity, namely conditional exchangeability; positivity; the same distributions of the versions of treatment; no interference; and no measurement error. We also require correct model specification. Under these conditions, we discuss how a version of direct standardization (the g-formula, adjustment formula, or transport formula) or inverse probability weighting can be used to generalize a causal effect from a study sample to a well-defined target population, and demonstrate their application in an illustrative example.
在流行病学研究中，人们会格外小心以确保因果效应估计的内部有效性；然而，外部有效性受到的关注则少得多。当研究样本不是目标人群的随机样本时，即使样本平均治疗效应在内部是有效的，通常也不能期望它等于目标人群中的平均治疗效应。出于规划目的和决策而进行的效应估计的效用，将取决于由于内部和外部有效性问题而导致的与目标人群中真实因果效应的偏离程度。在此，我们使用潜在结果框架，回顾近期文献中关于可推广性（外部有效性的一个方面）的概念。足以保证外部有效性的识别条件与内部有效性的识别条件非常相似，即条件可交换性；正性；治疗版本的相同分布；无干扰；以及无测量误差。我们还要求模型设定正确。在这些条件下，我们讨论如何使用直接标准化的一种形式（g 公式、调整公式或传递公式）或逆概率加权，将因果效应从研究样本推广到明确界定的目标人群，并在一个示例中展示它们的应用。
