Testing recursive path models with correlated errors using D-separation

被引:35
作者
Shipley, B [1 ]
机构
[1] Univ Sherbrooke, Dept Biol, Sherbrooke, PQ J1K 2R1, Canada
来源
STRUCTURAL EQUATION MODELING | 2003年 / 10卷 / 02期
基金
加拿大自然科学与工程研究理事会;
关键词
D O I
10.1207/S15328007SEM1002_3
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This article shows how to extend the inferential test of Shipley (2000b), which is applicable to recursive path models without correlated errors (a directed acyclic graph [DAG] model), to a class of recursive path models that include correlated errors (a semi-Markov model). The path model is first converted to a partial ancestral graph (PAG) and then, for PAGs that do not require latent variables, an inducing path DAG is obtained that is equivalent in its conditional independence relations to the original path model. The null probabilities of the k tests of independence that are implied by this DAG are combined using Fisher's test statistic C = -2SigmaLn(p(i)), which is distributed as a chi-square variate with 2k degrees of freedom.
引用
收藏
页码:214 / 221
页数:8
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