A New Identification Condition for Recursive Models With Correlated Errors

97 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

The Causal Foundations of Structural Equation Modeling (2012, methodology): “For example, a sufficient model-identification condition resulting from these techniques is the “non-bow rule” (Brito and Pearl, 2002b), i.”
Global identifiability of linear structural equation models (2010, background): “Other recent work, such as [3], considers a weaker identifiability requirement for the model M(G) associated with a mixed graph G = (V ,D,B).”
Identification and Likelihood Inference for Recursive Linear Models with Correlated Errors (2006, unknown): “An interpretation based on interventions has been proposed by Dawid [13], Lauritzen [33], Pearl [45], Spirtes et al. [56].”
Two Rules of Identification for Structural Equation Models (2009, background): “…necessary and sufficient condition of model identification is available, although various rules of identification exist for special types of structural equation models (e.g., Bollen, 1989, pp. 104, 247, 332; Brito & Pearl, 2002; Davis, 1993; O’Brien, 1994; Reilly & O’Brien, 1996; Rigdon, 1995).”