Factor analysis is one of the success stories of statistics in the social sciences. The reason for its wide appeal is that it provides a way to investigate latent variables, the fundamental traits and concepts in the study of individual differences. Because of its importance, a conference was held to mark the centennial of the publication of Charles Spearman's seminal 1904 article which introduced the major elements of this invaluable statistical tool. This book evolved from that conference. It provides a retrospective look at major issues and developments as well as a prospective view of future directions in factor analysis and related methods. In so doing, it demonstrates how and why factor analysis is considered to be one of the methodological pillars of behavioral research. Featuring an outstanding collection of contributors, this volume offers unique insights on factor analysis and its related methods. Several chapters have a clear historical perspective, while others present new ideas along with historical summaries. In addition, the book reviews some of the extensions of factor analysis to such techniques as latent growth curve models, models for categorical data, and structural equation models. Factor Analysis at 100 will appeal to graduate students and researchers in the behavioral, social, health, and biological sciences who use this technique in their research. A basic knowledge of factor analysis is required and a working knowledge of linear algebra is helpful.
Author(s): Robert Cudeck, Robert C. MacCallum
Edition: 1
Publisher: Routledge Academic
Year: 2007
Language: English
Pages: 402
Tags: Математика;Теория вероятностей и математическая статистика;Математическая статистика;Прикладная математическая статистика;
Front cover......Page 1
Contents......Page 8
Preface......Page 10
Acknowledgments......Page 14
CHAPTER 1. Factor Analysis in the Year 2004: Still Spry at 100......Page 16
CHAPTER 2. Three Faces of Factor Analysis......Page 24
CHAPTER 3. Remembering L. L. Thurstone......Page 38
CHAPTER 4. Rethinking Thurstone......Page 50
CHAPTER 5. Factor Analysis and Its Extensions......Page 62
CHAPTER 6. On the Origins of Latent Curve Models......Page 94
CHAPTER 7. Five Steps in the Structureal Factor Analysis of Longitudinal Data......Page 114
CHAPTER 8. Factorial Invariance: Historical Perspectives and New Problems......Page 146
CHAPTER 9. Factor Analysis Models as Approximations......Page 168
CHAPTER 10. Common Factors Versus Components: Principals and Principles, Errors and Misconceptions......Page 192
CHAPTER 11. Understanding Human Intelligence Since Spearman......Page 220
CHAPTER 12. Factoring at the Individual Level: Some Matters for the Second Century of Factor Analysis......Page 264
CHAPTER 13. Developments in the Factor Analysis of Individual Time Series......Page 280
CHAPTER 14. Factor Analysis and Latent Structure of Categorical and Metric Data......Page 308
CHAPTER 15. Rotation Methods, Algorithms, and Standard Errors......Page 330
CHAPTER 16. A Review of Nonlinear Factor Analysis and Nonlinear Structural Equation Modeling......Page 352
Contributors......Page 378
Author Index......Page 384
Subject Index......Page 392
Back cover......Page 402