<ul> <li>I. MULTIPLE REGRESSION. </li> <li>1. Introduction and Simple (Bivariate) Regression. </li> <li>2. Multiple Regression: Introduction. </li> <li>3. Multiple Regression: More Detail. </li> <li>4. Three and More Independent Variables and Related Issues. </li> <li>5. Three Types of Multiple Regression. </li> <li>6. Analysis of Categorical Variables. </li> <li>7. Categorical and Continuous Variables. </li> <li>8. Continuous Variables: Interactions and Curves. </li> <li>9. Multiple Regression: Summary, Further Study, and Problems. </li> <li>II. BEYOND MULTIPLE REGRESSION. </li> <li>10. Path modeling: Structural equation modeling with measured variables. </li> <li>11. Path Analysis: Dangers and Assumptions. </li> <li>12. Analyzing Path Models Using SEM Programs. </li> <li>13. Error: The Scourge of Research. </li> <li>14. Confirmatory Factor Analysis. </li> <li>15. Putting It All Together: Introduction to Latent Variable SEM. </li> <li>16. Latent Variable Models: More Advanced Topics. </li> <li>17. Summary: Path Analysis, CFA, and SEM. </li> <li>18. Appendices. </li> <li>19. References.</li> </ul>