A First Course in Structural Equation Modeling

A First Course in Structural Equation Modeling

A First Course in Structural Equation Modeling

A First Course in Structural Equation Modeling

Synopsis

This book is designed to introduce students to the basics of structural equation modeling through a conceptual, nonmathematical approach. The few mathematical formulas included are used in a conceptual or illustrative nature, rather than a computational one. The book features examples from LISREL and EQS. For that reason, the book can also be used as a beginning guide to learning how to set up input files to fit the most commonly used types of structural equation models with these programs. Intended as an introduction for graduate students or researchers in psychology, education, business, and other applied social and health sciences. The only prerequisite is a basic statistics course.

Excerpt

We wrote this book for an introductory structural equation modeling (SEM) course similar to the ones we teach at Fordham University and California State University, Fullerton. Our goal is to present a conceptual and nonmathematical introduction to sem methodology. the readership we have in mind consists mainly of graduate students or researchers from any discipline with limited or no previous exposure to sem. When we examined other available books, we found that most of them had serious limitations that precluded their use in an introductory course. These books were either too technical for beginners, did not cover in sufficient breadth the basics of the methodology that we consider to be relevant for this type of course, or intermixed fairly advanced issues with basic ones. Our book is therefore an alternative attempt to provide a first course in sem methodology at a coherent introductory level.

There are no special prerequisites for readers of this text beyond a course in basic statistics that included coverage of regression analysis. Because we frequently draw a parallel between aspects of sem and their apparent analogs in regression, this prior knowledge is important. There are also only a few mathematical formulas used, which are either conceptual or illustrative rather than computational in nature. Although the basic ideas and methods for conducting sem analyses presented in this book are independent of the particular computer programs used, for clarity the examples are illustrated using the two apparently most widely circulated programs, lisrel and eqs. As such, the book can also be used as a first guide for learning how to set up input files to fit several frequently used types of structural equation models with these programs.

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