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Exploratory Factor Analysis with SAS

Book Description

Explore the mysteries of Exploratory Factor Analysis (EFA) with SAS with an applied and user-friendly approach. Exploratory Factor Analysis with SAS focuses solely on EFA, presenting a thorough and modern treatise on the different options, in accessible language targeted to the practicing statistician or researcher. This book provides real-world examples using real data, guidance for implementing best practices in the context of SAS, interpretation of results for end users, and it provides resources on the book's author page. Faculty teaching with this book can utilize these resources for their classes, and individual users can learn at their own pace, reinforcing their comprehension as they go. Exploratory Factor Analysis with SAS reviews each of the major steps in EFA: data cleaning, extraction, rotation, interpretation, and replication. The last step, replication, is discussed less frequently in the context of EFA but, as we show, the results are of considerable use. Finally, two other practices that are commonly applied in EFA, estimation of factor scores and higher-order factors, are reviewed. Best practices are highlighted throughout the chapters. A rudimentary working knowledge of SAS is required but no familiarity with EFA or with the SAS routines that are related to EFA is assumed. Using SAS University Edition? You can use the code and data sets provided with this book. This helpful link will get you started: http://support.sas.com/publishing/import_ue.data.html

Table of Contents

  1. Title Page
  2. Copyright
  3. About This Book
  4. About the Author
  5. Chapter 1: Introduction to Exploratory Factor Analysis
    1. A Tool for Exploration
    2. EFA vs PCA
    3. Steps to Follow When Conducting EFA
    4. Basic Syntax for EFA
    5. Summary
    6. References
    7. End Notes
  6. Chapter 2: Extraction Method
    1. What Is Extraction?
    2. Key Concepts
    3. Extraction Techniques
    4. Three Pedagogical Examples
    5. Example Syntax and Output
    6. Does Extraction Method Matter?
    7. Summary
    8. Exercises
    9. Instruments Used in Examples
    10. References
    11. End Notes
  7. Chapter 3: Factor Extraction Criteria
    1. How Many Factors?
    2. Extraction Criteria
    3. Example Syntax and Output
    4. How Do the Criteria Compare?
    5. Summary
    6. Exercises
    7. References
    8. End Notes
  8. Chapter 4: Rotation
    1. The Magic of Rotation
    2. Types of Rotation
    3. Orthogonal vs Oblique Rotation
    4. Interpretation of Factor Matrices
    5. Example Syntax and Output
    6. Which Method?
    7. Exploring Multiple Solutions
    8. Summary
    9. Exercises
    10. References
    11. End Notes
  9. Chapter 5: Sample Size Matters
    1. Why Is Sample Size Important?
    2. Published Guidelines
    3. Sample Size in Practice
    4. An Empirical Investigation in Sample Size
    5. An Applied Example from Costello & Osborne
    6. Application: Impact of Sample Size on Interpretation
    7. Summary
    8. Exercises
    9. References
    10. End Notes
  10. Chapter 6: Replication Statistics
    1. Importance of Replication
    2. Let’s Bring Replication to EFA
    3. Procedural Aspects of Replicability Analysis
    4. Quantifying Replicability in EFA
    5. Application: Replication of Marsh SDQ Data
    6. Summary
    7. Exercises
    8. References
    9. End Notes
  11. Chapter 7: Bootstrap Applications
    1. How Does Bootstrap Resampling Fit into EFA?
    2. The Rise of Resampling
    3. Bootstrap Resampling Methods
    4. What Can Bootstrap Resampling Do, and What Should It Not Be Used For?
    5. Example Syntax and Output
    6. Application
    7. Summary
    8. Exercises
    9. References
    10. End Notes
  12. Chapter 8: Data Cleaning
    1. The Importance of Data Cleaning
    2. Outliers
    3. Application: Random vs Constant Responding
    4. Missing Data
    5. Application: Nonrandom Missingness and Imputation
    6. Summary
    7. Exercises
    8. References
    9. End Notes
  13. Chapter 9: Factor Scores
    1. Factor Scores 101
    2. Example Syntax and Output
    3. Application: Factor Score Estimation
    4. What Are Modern Alternatives?
    5. Summary
    6. Exercises
    7. References
    8. End Notes
  14. Chapter 10: Higher-Order Factors
    1. What Is a Higher-Order Factor?
    2. Did the Initial Solution Get It Right?
    3. Mechanics of Performing Second-Order Factor Analysis
    4. Application: Replication of Second-Order Factor
    5. Summary
    6. Exercises
    7. References
    8. End Notes
  15. Chapter 11: After the EFA: Internal Consistency
    1. What Comes Next?
    2. What Is Cronbach’s Alpha (And What Is It Not)?
    3. What Is “Good Enough” for Alpha?
    4. Factors That Influence Alpha and Its Use
    5. Estimation of Alpha in SAS
    6. Would Error-Free Measurement Make a Real Difference?
    7. Application
    8. Summary
    9. Exercises
    10. References
    11. End Notes
  16. Chapter 12: Summary and Conclusions
    1. Best Practices for EFA
    2. References
    3. End Notes
  17. Index
  18. Additional Resources