Foundations of Factor Analysis

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A01=Stanley A Mulaik
advanced factor analysis techniques
Author_Stanley A Mulaik
Category=JHBC
Category=JMB
Category=PBT
cients
coef
Common Factor Analysis
Common Factor Analysis Model
Common Factor Model
Common Factor Space
Composite Variables and Linear Transformations
Con Rmatory Factor Analyses
Coordinate Hyperplanes
Correlation Coef Cient
Correlation Matrix
diagonal
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Factor Indeterminacy
Factor Pattern Matrices
Factor Pattern Matrix
Factor Structure Matrix
GFI Index
gradient projection algorithm
Ij Ik
latent variable modeling
matrix
maximum likelihood estimation
Multiple and Partial Correlations
Multitrait Multimethod Correlation Matrix
Multivariate Normal Distibution
Oblique Analytic Rotation
Observed Variables
Orthogonal Analytic Rotation
Pa Method
pattern
Principal Axes Method
psychometrics
random
Reduced Correlation Matrix
Reference Vectors
Reliability Coef Cients
simple
Simple Structure Solution
solution
statistical data analysis
structural equation modeling
structure
Unique Factor Variances
Variance Covariance Matrix
vector
Xed Parameters

Product details

  • ISBN 9781420099614
  • Weight: 907g
  • Dimensions: 156 x 234mm
  • Publication Date: 25 Sep 2009
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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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.

Stanley A. Mulaik is a Professor Emeritus in the School of Psychology at the Georgia Institute of Technology.

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