Principles and Practice of Structural Equation Modeling / Edition 1

Principles and Practice of Structural Equation Modeling / Edition 1

by Rex B. Kline
     
 

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ISBN-10: 1572303379

ISBN-13: 9781572303379

Pub. Date: 05/27/1998

Publisher: Guilford Publications, Inc.

Designed for students and researchers without an extensive quantitative background, this book offers an informative guide to the application, interpretation, and pitfalls of structural equation modeling (SEM) in the social sciences. This is an accessible volume which covers introductory techniques, including path analysis and confirmatory factor analysis, and

Overview

Designed for students and researchers without an extensive quantitative background, this book offers an informative guide to the application, interpretation, and pitfalls of structural equation modeling (SEM) in the social sciences. This is an accessible volume which covers introductory techniques, including path analysis and confirmatory factor analysis, and provides an overview of more advanced methods, such as the evaluation of nonlinear effects, the analysis of means in covariance structure models, and latent growth models for longitudinal data. Providing examples from various disciplines to illustrate all aspects of SEM, the author offers clear instructions on the preparation and screening of data, common mistakes to avoid, and features of widely used software programs (Amos, EQS, and LISREL). Readers will acquire the skills necessary to begin to use SEM in their own research and to interpret and critique the use of the method by others.

Product Details

ISBN-13:
9781572303379
Publisher:
Guilford Publications, Inc.
Publication date:
05/27/1998
Series:
Methodology In The Social Sciences Series
Edition description:
Older Edition
Pages:
354
Product dimensions:
6.00(w) x 9.00(h) x (d)

Table of Contents

Contents
I. Fundamental Concepts
1. Introduction
2. Basic Statistical Concepts
3. SEM Family Tree
4. Data Preparation and Screening
II. Core SEM Techniques
5. Structural Models with Observed Variables and Path Analysis: I. Fundamentals, Recursive Models
6. Structural Models with Observed Variables and Path Analysis: II. Nonrecursive Models, Multiple Group Analysis
7. Measurement Models and Confirmatory Factor Analysis
8. Hybrid Models with Structural and Measurement Components
III. Avoiding Mistakes; Advanced Techniques; Software
9. How to Fool Yourself with SEM
10. Other Horizons: Overview of Advanced Techniques
11. Software for SEM: Amos, EQS, and LISREL

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