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Basic Principles of Structural Equation Modeling - An Introduction to LISREL and EQS (Hardcover, 1st ed. 1996. Corr. 2nd printing 1999)
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Basic Principles of Structural Equation Modeling - An Introduction to LISREL and EQS (Hardcover, 1st ed. 1996. Corr. 2nd printing 1999)
Series: Springer Texts in Statistics
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During the last two decades, structural equation modeling (SEM) has
emerged as a powerful multivariate data analysis tool in social
science research settings, especially in the fields of sociology,
psychology, and education. Although its roots can be traced back to
the first half of this century, when Spearman (1904) developed
factor analysis and Wright (1934) introduced path analysis, it was
not until the 1970s that the works by Karl Joreskog and his
associates (e. g., Joreskog, 1977; Joreskog and Van Thillo, 1973)
began to make general SEM techniques accessible to the social and
behavioral science research communities. Today, with the
development and increasing avail ability of SEM computer programs,
SEM has become a well-established and respected data analysis
method, incorporating many of the traditional analysis techniques
as special cases. State-of-the-art SEM software packages such as
LISREL (Joreskog and Sorbom, 1993a, b) and EQS (Bentler, 1993;
Bentler and Wu, 1993) handle a variety of ordinary least squares
regression designs as well as complex structural equation models
involving variables with arbitrary distributions. Unfortunately,
many students and researchers hesitate to use SEM methods, perhaps
due to the somewhat complex underlying statistical repre sentation
and theory. In my opinion, social science students and researchers
can benefit greatly from acquiring knowledge and skills in SEM
since the methods-applied appropriately-can provide a bridge
between the theo retical and empirical aspects of behavioral
research."
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