ABSTRACT

Path models, expressed as Directed Acyclic Graphs (DAGs), and the testing of such DAGs via a d-sep test, have become popular because they can incorporate complicated data structures that are difficult or impossible to accommodate in classical structural equation modeling. However, d-sep tests cannot accommodate DAGs that include unmeasured (latent) variables. We describe (i) how to convert a DAG with latent variables into an observationally equivalent graph without latents (a Mixed Acyclic Graph, MAG), (ii) how this MAG identifies which latents can/cannot be ignored without changing the causal meaning of the original DAG, and (iii) how to perform the MAG equivalent of a d-sep test.

摘要

表示为有向无环图 (DAG) 的路径模型以及通过 d-sep 测试对此类 DAG 进行测试已变得流行，因为它们可以合并在经典结构方程建模中难以或不可能容纳的复杂数据结构。但是，d-sep 测试无法容纳包含未测量（潜在）变量的 DAG。我们描述 (i) 如何将具有潜在变量的 DAG 转换为没有潜在变量的观察等效图（混合非循环图，MAG），（ii）该 MAG 如何识别哪些潜在变量可以/不能被忽略而不改变因果关系的含义原始 DAG，以及 (iii) 如何执行 d-sep 测试的 MAG 等效项。