Lesko Catherine R, Ackerman Benjamin, Webster-Clark Michael, Edwards Jessie K
Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD.
Department of Biostatistics, Johns Hopkins School of Public Health, Baltimore, MD.
Curr Epidemiol Rep. 2020 Sep;7(3):117-124. doi: 10.1007/s40471-020-00239-0. Epub 2020 Jun 30.
"Target bias" is the difference between an estimate of association from a study sample and the causal effect in the target population of interest. It is the sum of internal and external bias. Given the extensive literature on internal validity, here, we review threats and methods to improve external validity.
External bias may arise when the distribution of modifiers of the effect of treatment differs between the study sample and the target population. Methods including those based on modeling the outcome, modeling sample membership, and doubly robust methods are available, assuming data on the target population is available.
The relevance of information for making policy decisions is dependent on both the actions that were studied and the sample in which they were evaluated. Combining methods for addressing internal and external validity can improve the policy relevance of study results.
“目标偏倚”是指研究样本中关联估计值与目标感兴趣人群中的因果效应之间的差异。它是内部偏倚和外部偏倚的总和。鉴于关于内部效度的文献广泛，在此我们综述影响外部效度的因素及提高外部效度的方法。
当研究样本与目标人群中治疗效果修饰因素的分布不同时，可能会出现外部偏倚。假设可获得目标人群的数据，有多种方法可用，包括基于结局建模、样本成员建模和双重稳健方法。
用于制定政策决策的信息的相关性既取决于所研究的行动，也取决于评估这些行动的样本。综合解决内部效度和外部效度的方法可提高研究结果与政策的相关性。
