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This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using the open source software
R.
In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of
R and RStudio code, and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Dr. Watkins maintains an accessible tone throughout and uses minimal jargon and formula to help facilitate grasp of the key issues users will face while applying EFA, along with how to implement, interpret, and report results. Copious scholarly references and quotations are included to support the reader in responding to editorial reviews.
This is a valuable resource for upper-level undergraduate and postgraduate students, as well as for more experienced researchers undertaking multivariate or structure equation modeling courses across the behavioral, medical, and social sciences.
List of contents
Preface
1. Introduction
2. Data
3. R and RStudio Software
4. Importing and Saving Data and Results
5. Decision Steps in Exploratory Factor Analysis
6. Step 1: Variables to Include
7. Step 2: Participants
8. Step 3: Data Screening
9. Step 4: Is Exploratory Factor Analysis Appropriate
10. Step 5: Factor Analysis Model
11. Step 6: Factor Extraction Method
12. Step 7: How Many Factors to Retain
13. Step 8: Rotate Factors
14. Step 9: Interpret Exploratory Factor Analysis Results
15. Step 10: Report Exploratory Factor Analysis Results
16. Exploratory Factor Analysis with Categorical Variables
17. Higher-order and Bifactor Models
18. Exploratory Versus Confirmatory Factor Analysis
Practice Exercises
References and resources
About the author
Marley W. Watkins earned a Ph.D. in Educational Psychology and Measurements with a specialty in School Psychology from the University of Nebraska-Lincoln, USA. He is currently Research Professor in the Department of Educational Psychology at Baylor University, USA, and has authored more than 200 articles, books, and chapters and presented more than 150 papers at professional conferences.
Summary
This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using the open source software R.
