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Full Description
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.
Contents
Chapter1. An Introduction to Structural Equation Models.- Chapter2. Partial Least Squares Path Analysis.- Chapter3. Full-information Covariance SEM.- Chapter4. Systems of Regression Equations.- Chapter5. Data Collection, Control and Sample Size.- Chapter6. Survey and Questionnaire Data.- Chapter7. Research Structure and Paradigms.- Chapter8. Frontiers in Latent Variable Analysis.
