Providing a practical, thorough understanding of how factor analysis works, Foundations of Factor Analysis, 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.New to the Second EditionA new chapter on the multivariate normal distribution, its general properties, and the concept of maximum-likelihood estimationMore complete coverage of descriptive factor analysis and doublet factor analysisA rewritten chapter on analytic oblique rotation that focuses on the gradient projection algorithm and its applicationsDiscussions on the developments of factor score indeterminacyA revised chapter on confirmatory factor analysis that addresses philosophy of science issues, model specification and identification, parameter estimation, and algorithm derivationPresenting 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.
I recommend reading in conjunction with Principal Component Analysis by Jolliffe if you are interested in factor analysis for psychometrics. This book gives the psychologist's view of things and the history of factor analysis methods. Jolliffe gives a clearer mathematical presentation while approaching things like a statistician. Also, to get the most out of this book, know some linear algebra because the author is really heavy on matrix algebra.