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Basics of Structural Equation Modeling
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Basics of Structural Equation Modeling



328 pages | SAGE Publications, Inc
With the availability of software programs, such as LISREL, EQS, and AMOS, modelling (SEM) techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and test for the plausibility of the hypothesizing for a particular data set. However, the popularity of these techniques has often led to misunderstandings of them and even their misuse, particularly by students exposed to them for the first time. Through the use of careful narrative explanation, Maruyama's text describes the logic underlying SEM approaches, describes how SEM approaches relate to techniques like regression and factor analysis, analyzes the strengths and shortcomings of SEM as compared to alternative methodologies, and explores the various methodologies for analyzing structural equation data. In addition, Maruyama provides carefully constructed exercises both within and at the end of chapters.
 
PART ONE: BACKGROUND
 
What Does It Mean to Model Hypothesized Causal Processes with Nonexperimental Data?
 
History and Logic of Structural Equation Modeling
 
PART TWO: BASIC APPROACHES TO MODELING WITH SINGLE OBSERVED MEASURES OF THEORETICAL VARIABLES
 
The Basics
Path Analysis and Partitioning of Variance

 
 
Effects of Collinearity on Regression and Path Analysis
 
Effects of Random and Nonrandom Error on Path Models
 
Recursive and Longitudinal Models
Where Causality Goes in More Than One Direction and Where Data Are Collected Over Time

 
 
PART THREE: FACTOR ANALYSIS AND PATH MODELING
 
Introducing the Logic of Factor Analysis and Multiple Indicators to Path Modeling
 
PART FOUR: LATENT VARIABLE STRUCTURAL EQUATION MODELS
 
Putting It All Together
Latent Variable Structural Equation Modeling

 
 
Using Latent Variable Structural Equation Modeling to Examine Plausability of Models
 
Logic of Alternative Models and Significance Tests
 
Variations on the Basic Latent Variable Structural Equation Model
 
Wrapping up

"Overall, the book is a well-written introduction to structural equation modelling for people with a non-mathematical background. The stress is put on the logic of structural equation modelling and therefore it might be appreciated by more mathematical trained statisticians as well." 

Oliver Thas
The Statistician

"This book is a gentle introduction to the topic of structural equation modelling." 

Richard A. Chechile
Tufts University

Geoffrey M. Maruyama

My interest in what happens in diverse urban schools began when I became involved in a study of school desegregation while in graduate school. Those interests have led me to study a range of issues in schools, including school schedules and structures, teaching approaches such as cooperative learning and conflict resolution, social influence processes, and student background characteristics including poverty, type of housing, language, ability, and race/ethnicity. This work has been facilitated by time I spent in the Saint Paul Public Schools as their director of research, evaluation and assessment. Recently, my work has moved beyond... More About Author

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