Table of Contents
Preface
Part I: Multiple Regression
Chapter 1: Simple Bivariate Regression
Chapter 2: Multiple Regression: Introduction
Chapter 3: Multiple Regression: More Depth
Chapter 4: Three and More Independent Variables and Related Issues
Chapter 5: Three Types of Multiple Regression
Chapter 6: Analysis of Categorical Variables
Chapter 7: Regression with Categorical and Continuous Variables
Chapter 8: Testing for Interactions and Curves with Continuous Variables
Chapter 9: Mediation, Moderation, and Common Cause
Chapter 10: Multiple Regression: Summary, Assumptions, Diagnostics, Power, and Problems
Chapter 11: Related Methods: Logistic Regression and Multilevel Modeling
Part II: Beyond Multiple Regression: Structural Equation Modeling
Chapter 12: Path Modeling: Structural Equation Modeling with Measured Variables
Chapter 13: Path Analysis: Assumptions and Dangers
Chapter 14: Analyzing Path Models Using SEM Programs
Chapter 15: Error: The Scourge of Research
Chapter 16: Confirmatory Factor Analysis I
Chapter 17: Putting It All Together: Introduction to Latent Variable SEM
Chapter 18: Latent Variable Models II: Multigroup Models, Panel Models, Dangers & Assumptions
Chapter 19: Latent Means In SEM
Chapter 20: Confirmatory Factor Analysis II: Invariance and Latent Means
Chapter 21: Latent Growth Models
Chapter 22: Latent Variable Interactions and Multilevel Models In SEM
Chapter 23: Summary: Path Analysis, CFA, SEM, Mean Structures, and Latent Growth Models
Appendices
Appendix A: Data Files.
Appendix B: Review of Basic Statistics Concepts
Appendix C: Partial and Semipartial Correlation
Appendix D: Symbols Used in This Book
Appendix E: Useful Formulae