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Basics of Structural Equation Modeling
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Basics of Structural Equation Modeling


September 1997 | 328 pages | SAGE Publications, Inc

With the availability of software programs such as LISREL, EQS, and AMOS modeling techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and for testing the plausibility of hypothesizing for a particular data set. The popularity of these techniques, however, has often led to misunderstandings of them, particularly by students being exposed to them for the first time. Through the use of careful narrative explanation, Basics of Structural Equation Modeling describes the logic underlying structural equation modeling (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.


 
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

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