观察性研究中的因果图和混杂因素的识别和选择准则

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【中图分类号】 【文献标识码】A

【Abstract】 In observational research，a primary objective is to accurately and reliably assess the causal impact of exposure on outcomes. Identifying and properly adjusting for confounding factors is a key prerequisite and central challenge to achieving this goal. Ineffective management of confounders，whether by neglecting significant ones， （leading to residual confounding），or by over-adjusting for irrelevant factors， （introducing collider bias），can distort effect estimates and lead to erroneous scientific conclusions and clinical decisions. Therefore， it is essential to develop and implement systematic，transparent，and reproducible methods for identifying and selecting confounding factors to enhance the validity and reliability of causal inferences in observational studies.This paper provides a systematic review of directed acyclic graphs （DAGs）， a robust visual causal modeling tool，and offers a detailed examination of three prominent criteria for selecting confounding factors based on DAGs：the Pre-exposure criterion，the Common causecriterion，and the Modified disjunctive cause criterion.The aim is to equip researchers with a structured and theoretically grounded framework for identifying and selecting confounding factors，thereby improving the process of estimating causal effects in observational studies.

【Keywords】Confounders; Confounding; Directed acyclic graphs; Pre-exposure criterion; Common cause criterion; Modified disjunctive cause criterion

开展随机对照试验存在伦理约束、研究成本（时间、经济等）较高、受试者纳排标准严苛，受试者招募困难等问题[1-3]。（剩余11498字）