 
Summary: 1
Using Path Diagrams as a Structural Equation Modelling
Tool
by Peter Spirtes, Thomas Richardson, Chris Meek, Richard Scheines,
and Clark Glymour
1. Introduction
Linear structural equation models (SEMs) are widely used in sociology, econometrics,
biology, and other sciences. A SEM (without free parameters) has two parts: a probability
distribution (in the Normal case specified by a set of linear structural equations and a
covariance matrix among the ``error'' or ``disturbance'' terms), and an associated path
diagram corresponding to the functional composition of variables specified by the structural
equations and the correlations among the error terms. It is often thought that the path
diagram is nothing more than a heuristic device for illustrating the assumptions of the
model. However, in this paper, we will show how path diagrams can be used to solve a
number of important problems in structural equation modelling.
There are a number of problems associated with structural equation modeling. These
problems include:
. How much do sample data underdetermine the correct model specification? Of
course, one must decide how much credence to give alternative explanations that afford
different fits to any particular data set. There are a variety of techniques for that purpose,
