Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis, 4th Edition (Paperback) book cover

Latent Variable Models

An Introduction to Factor, Path, and Structural Equation Analysis, 4th Edition

By John C. Loehlin

© 2004 – Psychology Press

332 pages

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pub: 2003-12-03
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About the Book

This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp the underlying relationships between path analysis, factor analysis, and structural equation modeling more easily. A few sections of the book make use of elementary matrix algebra. An appendix on the topic is provided for those who need a review. The author maintains an informal style so as to increase the book's accessibility. Notes at the end of each chapter provide some of the more technical details. The book is not tied to a particular computer program, but special attention is paid to LISREL, EQS, AMOS, and Mx.

New in the fourth edition of Latent Variable Models:

*a data CD that features the correlation and covariance matrices used in the exercises;

*new sections on missing data, non-normality, mediation, factorial invariance, and automating the construction of path diagrams; and

*reorganization of chapters 3-7 to enhance the flow of the book and its flexibility for teaching.

Intended for advanced students and researchers in the areas of social, educational, clinical, industrial, consumer, personality, and developmental psychology, sociology, political science, and marketing, some prior familiarity with correlation and regression is helpful.


"Overall this is an excellent book and has served as a standard textbook for many years….The section on power is really terrific….Loehlin addresses complex topics very clearly."

Jodie Ullman, Ph.D.

California State University, San Bernadino

"The uniqueness of Loehlin's book is to mainly use path diagrams with minimum or no equations in presenting the structural equation model (SEM) and factor analysis (FA) model. This is good for students who do not have a lot of statistical or mathematical background."

Ke-Hai Yuan, Ph.D.

Notre Dame University

Table of Contents

Contents: Preface. Path Models in Factor, Path, and Structural Equation Analysis. Fitting Path Models. Fitting Path and Structural Models to Data From a Single Group on a Single Occasion. Fitting Models Involving Repeated Measures or Multiple Groups. Exploratory Factor Analysis--Basics. Exploratory Factor Analysis--Elaborations. Issues in the Application of Latent Variable Analysis. Appendices.

Subject Categories

BISAC Subject Codes/Headings:
EDUCATION / Statistics
PSYCHOLOGY / Research & Methodology
PSYCHOLOGY / Statistics