Latent Variable Models is a simply tremendous statistics book. It is masterfully, and authoritatively written, with a touch of humor here and there. It is -- by far -- the best book on structural equations and related models.
Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis
β Scribed by John C. Loehlin
- Publisher
- Routledge Academic
- Year
- 2003
- Tongue
- English
- Leaves
- 330
- Edition
- 4
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.
β¦ Table of Contents
Cover
......Page 1
Half-title
......Page 2
Title
......Page 4
Copyright
......Page 5
Contents
......Page 6
Preface
......Page 10
1. Path models in factor, path, and structural equation analysis
......Page 14
2. Fitting path models
......Page 48
3. Fitting path and structural models to data from a single group on a single occasion
......Page 100
4. Fitting models involving repeated measures or multiple groups
......Page 133
5. Exploratory factor analysisβbasics
......Page 165
6. Exploratory factor analysisβelaborations
......Page 200
7. Issues in the application of latent variable models
......Page 226
Appendix a: a simple matrix operations
......Page 251
Appendix b: derivation of matrix version of path equations
......Page 258
Appendix c: LISREL matrices and examples
......Page 260
Appendix d: various goodness-of-fit indices
......Page 264
Appendix e: phatom variables
......Page 271
Appendix f: data matrix for Thurstone's box problem
......Page 273
Appendix g: table of chi square
......Page 275
Appendix h: noncentral chi square for estimating power
......Page 276
Appendix i: power of a test of poor fit and sample sizes needed for power of .80 and .90
......Page 277
Answers to exercises
......Page 278
References
......Page 289
Index
......Page 322
π SIMILAR VOLUMES
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
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
Latent Variable Models is a simply tremendous statistics book. It is masterfully, and authoritatively written, with a touch of humor here and there. It is -- by far -- the best book on structural equations and related models.