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Exploratory Factor Analysis
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A firm knowledge of factor analysis is key to understanding much published research in the social and behavioral sciences. Exploratory Factor Analysis by W. Holmes Finch provides a solid foundation in exploratory factor analysis (EFA), which along with confirmatory factor analysis, represents one of the two major strands in this field. The book lays out the mathematical foundations of EFA; explores the range of methods for extracting the initial factor structure; explains factor rotation; and outlines the methods for determining the number of factors to retain in EFA. The concluding chapter addresses a number of other key issues in EFA, such as determining the appropriate sample size for a given research problem, and the handling of missing data.  It also offers brief introductions to exploratory structural equation modeling, and multilevel models for EFA. Example computer code, and the annotated output for all of the examples included in the text are available on an accompanying website. 

 
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

 

Supplements

Resource Center
Example computer code, and the annotated output for all of the examples included in the text are available on the accompanying website.

This text is a perfect resource for individuals seeking guidance on applied factor analysis, covering the fundamentals as well as introductions to more advanced aspects of factor analytic techniques. 

Damon Cann
Utah State University
Review

Finch provides a well-written and well-organized introduction to the conceptual and quantitative topics of exploratory and confirmatory factor analysis within a single, concise text. 

Stephen G. Sapp
Iowa State University
Review

This is a thorough and readable introduction to exploratory factor analysis

Michael D. Biderman
University of Tennessee at Chattanooga
Review

Sample Materials & Chapters

Chapter 1:Introduction to Factor Analysis


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