A Step-by-Step Guide to Exploratory Factor Analysis with R and RStudio

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.DOI: 10.4324/9781003120001 Cover Endorsements Half Title Title Page Copyright Page Contents List of Figures Preface 1. Introduction Historical Foundations Conceptual Foundations Graphical Displays and Vocabulary 2. Data Dataset 1 Dataset 2 Dataset 3 Dataset 4 3. R and RStudio Software R and RStudio R Packages 4. Importing and Saving Data and Results Importing a Correlation Matrix Data Packages Saving Data Saving Results 5. Decision Steps in Exploratory Factor Analysis Flowchart of Decision Steps (Figure 5.1) Checklist of Decision Steps (Figure 5.2) 6. Step 1: Variables to Include Report 7. Step 2: Participants Characteristics of Participants Number of Participants Report 8. Step 3: Data Screening Assumptions Restricted Score Range Linearity Data Distributions Outliers Missing Data Report 9. Step 4: Is Exploratory Factor Analysis Appropriate Report 10. Step 5: Factor Analysis Model Report 11. Step 6: Factor Extraction Method Report 12. Step 7: How Many Factors to Retain Empirical Guidelines Theoretical Knowledge Model Selection Report 13. Step 8: Rotate Factors Orthogonal versus Oblique Rotation Factor Loadings Eigenvalues and Variance Extracted Report 14. Step 9: Interpret Exploratory Factor Analysis Results Model Selection Guidelines Report Model Evaluation Model 3 Model 2 Model 1 Factor Names Report 15. Step 10: Report Exploratory Factor Analysis Results Factor Scores Cautions 16. Exploratory Factor Analysis with Categorical Variables Data Participants Data Screening Is EFA Appropriate Factor Analysis Model Factor Extraction Method How Many Factors to Retain Rotate Factors Interpret Results 17. Higher-Order and Bifactor Models Higher-Order Models Schmid-Leiman Transformation of Higher-Order Models Bifactor Models Alternative Measures of Reliability 18. Exploratory versus Confirmatory Factor Analysis CFA Model Fit CFA Model Respecification CFA Model Assumptions Exploratory Use of CFA EFA versus CFA Practice Exercises Exercise 1 Data Variables Included Participants Is the Data Appropriate? Is EFA Appropriate? What Model of Factor Analysis Was Employed? What Factor Extraction Method Was Used? How Many Factors Were Retained? What Factor Rotation Was Applied? Interpretation of Results Report Results Exercise 1 Report Method Results Exercise 2 Data Are the Data Appropriate for EFA? Is EFA Appropriate? How Many Factor to Retain? Factor Models: Three Factors Factor Models: Two Factors Factor Models: One Factor Factor Models: Robustness Evaluation of Two-Factor Model References and Resources Index "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 when 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"-- Provided by publisher 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.