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
Chapter Two: Mathematical Underpinnings of Factor Analysis
Correlation and Covariance Matrices
Correspondence Between the Factor Model and the Covariance Matrix
Error Variance and Communalities
Chapter Three: Methods of Factor Extraction in Exploratory Factor Analysis
Eigenvalues, Factor Loadings, and the Observed Correlation Matrix
Principal Components Analysis
Principal Components Versus Factor Analysis
Other Factor Extraction Methods
Chapter Four: Methods of Factor Rotation
Orthogonal Versus Oblique Rotation Methods
Common Orthogonal Rotations
Deciding Which Rotation to Use
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
Chapter Six: Final Issues in Factor Analysis
Proper Reporting Practices for Factor Analysis
Power Analysis and A Priori Sample Size Determination
Dealing With Missing Data
Exploratory Structural Equation Modeling