Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
Eur J Endocrinol. 2020 May;182(5):E5-E7. doi: 10.1530/EJE-20-0075.
The results of observational studies of causal effects are potentially biased due to confounding. Various methods have been proposed to control for confounding in observational studies. Eight basic aspects of confounding adjustment are described, with a focus on correction for confounding through covariate adjustment using regression analysis. These aspects should be considered when planning an observational study of causal effects or when assessing the validity of the results of such a study.
观察性研究中因果效应的结果可能由于混杂而存在偏倚。已经提出了各种方法来控制观察性研究中的混杂。本文描述了混杂调整的 8 个基本方面,重点介绍了通过使用回归分析进行协变量调整来纠正混杂。在计划因果效应的观察性研究或评估此类研究结果的有效性时,应该考虑这些方面。