Structural Equation Models

From Paths to Networks

  • J. Christopher Westland

Part of the Studies in Systems, Decision and Control book series (SSDC, volume 22)

Table of contents

  1. Front Matter
    Pages i-ix
  2. J. Christopher Westland
    Pages 1-15
  3. J. Christopher Westland
    Pages 17-38
  4. J. Christopher Westland
    Pages 39-49
  5. J. Christopher Westland
    Pages 51-65
  6. J. Christopher Westland
    Pages 67-89
  7. J. Christopher Westland
    Pages 91-106
  8. J. Christopher Westland
    Pages 107-126
  9. J. Christopher Westland
    Pages 127-134
  10. Back Matter
    Pages 135-149

About this book


This new edition surveys the full range of available structural equation modeling (SEM) methodologies. The book has been updated throughout to reflect the arrival of new software packages, which have made analysis much easier than in the past. Applications in a broad range of disciplines are discussed, particularly in the social sciences where many key concepts are not directly observable. This book presents SEM’s development in its proper historical context–essential to understanding the application, strengths and weaknesses of each particular method. This book also surveys the emerging path and network approaches that complement and enhance SEM, and that are growing in importance. SEM’s ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists. Latent variable theory and application are comprehensively explained and methods are presented for extending their power, including guidelines for data preparation, sample size calculation and the special treatment of Likert scale data. Tables of software, methodologies and fit statistics provide a concise reference for any research program, helping assure that its conclusions are defensible and publishable.


Structural Equation Models (SEM) Partial Least Squares (PLS) LISREL-AMOS Systems of Regression Equations techniques for path analysis treatment of Likert scale data Likert scale categorical data latent variable constructs latent variables likert scales likert scale data path analysis structural equation models computer fitting data preparation for structural equation models

Authors and affiliations

  1. 1.Information & Decision SystemsUniversity of Illinois at ChicagoChicagoUSA

Bibliographic information