Using Path Diagrams as a Structural Equation Modeling Tool

Peter Spirtes, Thomas Richardson, Christopher Meek, Richard Scheines and Clark Glymour
Additional contact information
Peter Spirtes: Carnegie Mellon University
Thomas Richardson: University of Washington
Christopher Meek: Microsoft Corporation
Richard Scheines: Carnegie Mellon University
Clark Glymour: Carnegie Mellon University and the University of California, San Diego

Sociological Methods & Research, 1998, vol. 27, issue 2, 182-225

Abstract: A linear structural equation model (SEM) without free parameters has two parts: a probability distribution and an associated path diagram corresponding to the causal relations among variables specified by the structural equations and the correlations among the error terms. This article shows how path diagrams can be used to solve a number of important problems in structural equation modeling; for example, How much do sample data underdetermine the correct model specification? Given that there are equivalent models, is it possible to extract the features common to those models? When a modeler draws conclusions about coefficients in an unknown underlying SEM from a multivariate regression, precisely what assumptions are being made about the SEM? The authors explain how the path diagram provides much more than heuristics for special cases; the theory of path diagrams helps to clarify several of the issues just noted.

Date: 1998
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:somere:v:27:y:1998:i:2:p:182-225

DOI: 10.1177/0049124198027002003

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