Lawrence Erlbaum Associates, 2000. - 204 pages.
What Is Structural Equation Modeling? Structural equation modeling is a statistical methodology used by biologists, economists, educational researchers, marketing researchers, medical researchers, and a variety of social and behavioral scientists. One reason for its pervasive use in many scientific fields of study is that structural equation modeling provides researchers with a comprehensive method for the quantification and testing of theories. Other major characteristics of structural equation models are that they explicitly take into account the measurement error that is ubiquitous in most disciplines and contain latent variables.
Preface
We wrote this book for an introductory structural equation modeling (SEM) course similar to the ones we teach at Fordham University and Califoia 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 alteative attempt to provide a first course in SEM
methodology at a coherent introductory level.
What Is Structural Equation Modeling? Structural equation modeling is a statistical methodology used by biologists, economists, educational researchers, marketing researchers, medical researchers, and a variety of social and behavioral scientists. One reason for its pervasive use in many scientific fields of study is that structural equation modeling provides researchers with a comprehensive method for the quantification and testing of theories. Other major characteristics of structural equation models are that they explicitly take into account the measurement error that is ubiquitous in most disciplines and contain latent variables.
Preface
We wrote this book for an introductory structural equation modeling (SEM) course similar to the ones we teach at Fordham University and Califoia 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 alteative attempt to provide a first course in SEM
methodology at a coherent introductory level.