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Exploratory Factor Analysis
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


Error Variance and Communalities


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



Chapter Four: Methods of Factor Rotation
Simple Structure

Orthogonal Versus Oblique Rotation Methods

Common Orthogonal Rotations

Common Oblique Rotations

Target Factor Rotation

Bifactor Rotation


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

Parallel Analysis

Minimum Average Partial

Very Simple Structure



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




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

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

This is a thorough and readable introduction to exploratory factor analysis

Michael D. Biderman
University of Tennessee at Chattanooga

Sample Materials & Chapters

Chapter 1:Introduction to Factor Analysis

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