Structural Equation Modeling: Foundations and Extensions by David W. Kaplan

By David W. Kaplan

With exact, empirical examples, this fascinating publication provides a sophisticated remedy of the rules of structural equation modeling (SEM) and demonstrates how SEM offers a special lens on difficulties within the social and behavioral sciences. the writer starts with an advent to recursive and non-recursive types, estimation, checking out, and the matter of dimension in saw variables. Then Kaplan explores the difficulty of staff adjustments in structural types, statistical assumptions in structural modeling (from sampling to lacking info and specification error), the evaluate of statistical strength and version amendment within the context of version evaluate, and SEM utilized to advanced information buildings reminiscent of these bought from clustered random sampling.

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In addition, I would like to thank Kathleen Cimbolic, Jane Folske, Polina Havila, Melissa Houlette, Kelly Jackson, Michele Kreisman, Nicole Mott, Hyeon-Joo Oh, Hye-Sook Park, Linda Roades, and Kristen Schoff. They were students in my Fall 1999 Structural Modeling class and offered helpful comments on an earlier draft of this book. A special thanks goes to Karen Kral who provided expert assistance in helping to lay out the draft of this book. I would also like to thank Terri L. Belote and Renee Saxton-Forgue, proprietors of Brewed Awakenings in Newark, Delaware, for serving outstanding and much needed espresso throughout the development of this book.

However, the scope of this book simply does not admit the possibility of covering every new topic under the rubric of structural equation modeling. As I will outline below, new developments in structural equation modeling that I view as particularly exciting, will be covered in detail. Orientation The audiences for this book are advanced graduate students, substantive researchers, and methodologists in the social and behavioral sciences—particularly psychology, sociology, and education. The book is also suited to applied statisticians with interests in structural equation modeling.

2) was a major innovation in econometric modeling. 1 This group wedded the newly developed simultaneous equation model with the method of maximum likelihood estimation and associated hypothesis testing methodologies (see Hood & Koopmans, 1953; Koopmans, 1950). For the next 25 years, the thrust of econometric research was devoted to the refinement of the simultaneous equa- 1 As discussed in Berndt (1991), the Cowles Commission was founded by Alfred Cowles, III who, among other things, provided the resources necessary to create the Econometric Society.

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