Loehlin J.C. Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis

London: Routledge Academic, 2003. — 330 p. Метод анализа скрытых переменных является обобщением факторного анализа, метода структурных уравнений и анализа путей и находит широкое применение в экономических, психологических и социальных исследованиях.
Для изучающих многомерные статистические методы и их применения. 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
Simple matrix operations
Derivation of matrix version of path equations
LISREL matrices and examples
Various goodness-of-fit indices
Phantom variables
Data matrix for Thurstone's box problem
Table of Chi Square
Noncentral Chi Square for estimating power
Power of a test of poor fit and sample sizes needed for powers of .80 and .90
Answers to exercises
References
Index