Description
Foundations of Factor Analysis (2nd Ed.)
Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences Series
Author: Mulaik Stanley A
Language: EnglishSubjects for Foundations of Factor Analysis:
Keywords
Con Rmatory Factor Analyses; Factor Pattern Matrix; Composite Variables and Linear Transformations; GFI Index; Multiple and Partial Correlations; Common Factor Model; Multivariate Normal Distibution; Common Factor Analysis; Orthogonal Analytic Rotation; Simple Structure Solution; Oblique Analytic Rotation; Unique Factor Variances; Common Factor Analysis Model; Factor Structure Matrix; Variance Covariance Matrix; Ij Ik; Correlation Matrix; Observed Variables; Correlation Coef Cient; Principal Axes Method; Coordinate Hyperplanes; Pa Method; Reduced Correlation Matrix; Factor Indeterminacy; Reference Vectors; Reliability Coef Cients; Factor Pattern Matrices; Common Factor Space; Multitrait Multimethod Correlation Matrix; Xed Parameters
560 p. · 15.6x23.4 cm · Hardback
Description
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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 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.
Introduction. Mathematical Foundations for Factor Analysis. Composite Variables and Linear Transformations. Multiple and Partial Correlations. Multivariate Normal Distribution. Fundamental Equations of Factor Analysis. Methods of Factor Extraction. Common-Factor Analysis. Other Models of Factor Analysis. Factor Rotation. Orthogonal Analytic Rotation. Oblique Analytic Rotation. Factor Scores and Factor Indeterminacy. Factorial Invariance. Confirmatory-Factor Analysis. References. Indices.
Stanley A. Mulaik is a Professor Emeritus in the School of Psychology at the Georgia Institute of Technology.