Confounder selection is perhaps the most important step in the design of observational studies. A number of criteria, often with different objectives and approaches, have been proposed, and their validity and practical value have been debated in the literature. Here, we provide a unified review of these criteria and the assumptions behind them. We list several objectives that confounder selection methods aim to achieve and discuss the amount of structural knowledge required by different approaches. Finally, we discuss limitations of the existing approaches and implications for practitioners.

翻译：混杂因素筛选可能是观察性研究设计中最关键的步骤。已有多种标准被提出，这些标准通常具有不同的目标和方法，并在文献中对其有效性和实用价值进行了讨论。本文对这些标准及其背后的假设进行了统一梳理。我们列出了混杂因素筛选方法旨在实现的若干目标，并探讨了不同方法所需的结构性知识量。最后，我们讨论了现有方法的局限性及其对实践者的启示。