E-Book Overview
Providing a practical, thorough understanding of how factor analysis works,<STRONG> Foundations of Factor Analysis<STRONG>, <STRONG>Second Edition discusses the assumptions underlying the equations and procedures of this method. It also explains the options in commercial computer programs for performing factor analysis and structural equation modeling. This long-awaited edition takes into account the various developments that have occurred since the publication of the original edition.
<STRONG>New to the Second Edition
- A new chapter on the multivariate normal distribution, its general properties, and the concept of maximum-likelihood estimation
- More complete coverage of descriptive factor analysis and doublet factor analysis
- A rewritten chapter on analytic oblique rotation that focuses on the gradient projection algorithm and its applications
- Discussions on the developments of factor score indeterminacy
- A revised chapter on confirmatory factor analysis that addresses philosophy of science issues, model specification and identification, parameter estimation, and algorithm derivation
Presenting the mathematics only as needed to understand the derivation of an equation or procedure, this textbook prepares students for later courses on structural equation modeling. It enables them to choose the proper factor analytic procedure, make modifications to the procedure, and produce new results.
E-Book Content
Foundations of
Factor Analysis Second Edition
© 2010 by Taylor & Francis Group, LLC
Chapman & Hall/CRC
Statistics in the Social and Behavioral Sciences Series Series Editors A. Colin Cameron University of California, Davis, USA
J. Scott Long Indiana University, USA
Andrew Gelman Columbia University, USA
Sophia Rabe-Hesketh University of California, Berkeley, USA
Anders Skrondal Norwegian Institute of Public Health, Norway
Aims and scope Large and complex datasets are becoming prevalent in the social and behavioral sciences and statistical methods are crucial for the analysis and interpretation of such data. This series aims to capture new developments in statistical methodology with particular relevance to applications in the social and behavioral sciences. It seeks to promote appropriate use of statistical, econometric and psychometric methods in these applied sciences by publishing a broad range of reference works, textbooks and handbooks. The scope of the series is wide, including applications of statistical methodology in sociology, psychology, economics, education, marketing research, political science, criminology, public policy, demography, survey methodology and official statistics. The titles included in the series are designed to appeal to applied statisticians, as well as students, researchers and practitioners from the above disciplines. The inclusion of real examples and case studies is therefore essential.
Published Titles Analysis of Multivariate Social Science Data, Second Edition David J. Bartholomew, Fiona Steele, Irini Moustaki, and Jane I. Galbraith Bayesian Methods: A Social and Behavioral Sciences Approach, Second Edition Jeff Gill Foundations of Factor Analysis, Second Edition Stanley A. Mulaik Linear Causal Modeling with Structural Equations Stanley A. Mulaik Multiple Correspondence Analysis and Related Methods Michael Greenacre and Jorg Blasius Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences Brian S. Everitt Statistical Test Theory for the Behavioral Sciences Dato N. M. de Gruijter and Leo J. Th. van der Kamp © 2010 by Taylor & Francis Group, LLC
Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences Series
Foundations of
Factor Analysis Second Ed