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STRUCTURAL EQUATION MODELING, 13(3), 465–486
Copyright © , Lawrence Erlbaum Associates, Inc.
TEACHER’S CORNER
Structural Equation Modeling
With the semPackage in R
John Fox
McMaster University
R is free, open-source, cooperatively developed software that implements the S sta-
tistical programming language and computing environment. The current capabilities
of R are extensive, and it is in wide use, especially among statisticians. The sem
package provides basic structural equation modeling facilities in R, including the
ability to fit structural equations in observed variable models by two-stage least
squares, and to fit latent variable models by full information maximum likelihood as-
suming multinormality. This article briefly describes R, and then proceeds to illus-
trate the use of the tsls and sem functions in the sem package. The article also
demonstrates the integration of the sempackage with other facilities available in R,
for example for computing polychoric correlations and for bootstrapping.
R (Ihaka & Gentleman, 1996; R Development Core Team, ) is a free,
open-source, cooperatively developed implementation of the S statistical program-
ming language and computing environment (Becker, Chambers, & Wilks, 1988;
Chambers, 1998; Chambers & Hastie, 1992).1 Since its introduction in the
mid-1990s, R has rapidly become one of the most widely used facilities for statisti-
cal computing, especially among statisticians, and arguably now has broader cov-
erage of statistical methods than any other statistical software. The basic R system,
with capabilities roughly comparable to (say) a basic installation of SAS, can be
augmented by contributed packages, which now number more than 700. These
Correspond
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