Preface Part I: Multiple Regression Chapter 1: Simple Bivariate Regression Chapter 2: Multiple Regression: Introduction Chapter 3: Multiple Regression: More Detail 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. Appendices B: Review of Basic Statistics Concepts Appendix C: Partial and Semipartial Correlation Appendix D: Symbols Used in This Book Appendix E: Useful Formulae.