研究设计时混杂控制策略的结构分类

混杂影响着人群因果关系的发生。依据混杂因素是否已知、可测量及已测量，可将其分为4类情形。基于有向无环图，对混杂的控制策略分为两类：①混杂路径打断法，又可分为单路径和双路径打断法，分别对应于暴露完全干预法、限制法和分层法；②混杂路径保留法，分别对应于暴露不完全干预法（工具变量设计或不完美的随机对照试验）、中间变量法和匹配法。其中，随机对照试验、工具变量设计或孟德尔随机化设计、中间变量分析可满足4类混杂的控制，而限制法、分层法和匹配法仅适用于已知、可测量并已测量的混杂。识别不同类型混杂的控制机制，有助于在研究设计阶段提出应对措施，是获得正确因果效应估计的前提。

A structural classification of strategies for confounding control in research design

Confounding affects the causal relation among the population. Depending on whether the confounders are known, measurable or measured, they can be divided into four categories. Based on Directed Acyclic Graphs, the strategies for confounding control can be classified as (1) the broken-confounding-path method, which can be further divided into single and dual broken paths, corresponding to exposure complete intervention, restriction and stratification, (2) and the reserved-confounding-path method, which can be further divided into incomplete exposure intervention (in instrumental variable design and non-perfect random control test), mediator method and matching method. Among them, random control test, instrumental variable design or Mendelian randomized design, mediator method can meet the requirements for controlling all four types of confounders, while the restriction, stratification and matching methods are only applicable to known, measurable and measured confounders. Identifying the mechanisms of confounding control is a prerequisite for obtaining correct causal effect estimates, which will be helpful in research design.