论文标题
测量偏见：结构观点
Measurement bias: a structural perspective
论文作者
论文摘要
测量偏置（MB）的因果结构仍然存在争议。在有向的无环图（DAG）的帮助下，本文提出了一种用于测量一个单胎变量的新结构，该结构在选择不完美的I/O设备样测量系统时出现。但是，为了估计效应估计，MB的额外来源是由测得的暴露与测量结果之间的任何冗余关联产生的。对于共同结果，因果关系的单向差异，错误分类将是双向差异的，对于测量的暴露与测量结果或测量结果或无效效应之间的共同原因是非差异的。测得的暴露实际上会影响测得的结果，反之亦然。反向因果关系是在测量水平上定义的概念。我们的新DAG阐明了MB的结构和机制。
The causal structure for measurement bias (MB) remains controversial. Aided by the Directed Acyclic Graph (DAG), this paper proposes a new structure for measuring one singleton variable whose MB arises in the selection of an imperfect I/O device-like measurement system. For effect estimation, however, an extra source of MB arises from any redundant association between a measured exposure and a measured outcome. The misclassification will be bidirectionally differential for a common outcome, unidirectionally differential for a causal relation, and non-differential for a common cause between the measured exposure and the measured outcome or a null effect. The measured exposure can actually affect the measured outcome, or vice versa. Reverse causality is a concept defined at the level of measurement. Our new DAGs have clarified the structures and mechanisms of MB.
