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Basics of Structural Equation Modeling

Autor Geoffrey M. Maruyama
en Limba Engleză Electronic book text – 26 iun 2012
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.
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Specificații

ISBN-13: 9781452250205
ISBN-10: 1452250200
Pagini: 328
Dimensiuni: 152 x 229 mm
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Locul publicării:Thousand Oaks, United States

Recenzii

"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." 

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

Cuprins

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

Descriere

This text is designed to guide students through the logic underlying SEM approaches. It describes how SEM approaches relate to techniques like regression and factor analysis and analyzes the strengths and shortcomings of SEM as compared to alternative methodologies.