Chapter One: Introduction to Factor Analysis
Latent and Observed Variables
The Importance of Theory in Doing Factor Analysis
Comparison of Exploratory and Confirmatory Factor Analysis
EFA and Other Multivariate Data Reduction Techniques
A Brief Word About Software
Outline of the Book
Chapter Two: Mathematical Underpinnings of Factor Analysis
Correlation and Covariance Matrices
The Common Factor Model
Correspondence Between the Factor Model and the Covariance Matrix
Eigenvalues
Error Variance and Communalities
Summary
Chapter Three: Methods of Factor Extraction in Exploratory Factor Analysis
Eigenvalues, Factor Loadings, and the Observed Correlation Matrix
Maximum Likelihood
Principal Axis Factoring
Principal Components Analysis
Principal Components Versus Factor Analysis
Other Factor Extraction Methods
Example
Summary
Chapter Four: Methods of Factor Rotation
Simple Structure
Orthogonal Versus Oblique Rotation Methods
Common Orthogonal Rotations
Common Oblique Rotations
Target Factor Rotation
Bifactor Rotation
Example
Deciding Which Rotation to Use
Summary
Appendix
Chapter Five: Methods for Determining the Number of Factors to Retain in Exploratory Factor Analysis
Scree Plot and Eigenvalue Greater Than 1 Rule
Objective Methods Based on the Scree Plot
Eigenvalues and the Proportion of Variance Explained
Residual Correlation Matrix
Chi-Square Goodness of Fit Test for Maximum Likelihood
Parallel Analysis
Minimum Average Partial
Very Simple Structure
Example
Summary
Chapter Six: Final Issues in Factor Analysis
Proper Reporting Practices for Factor Analysis
Factor Scores
Power Analysis and A Priori Sample Size Determination
Dealing With Missing Data
Exploratory Structural Equation Modeling
Multilevel EFA
Summary