Part I: I need to do regression analysis tomorrow
| Chapter 1 | Building Models with Regression and Correlation |
| 1.1 | What are Models? |
| 1.2 | Least Squares Models |
| 1.3 | Modelling Relationships |
| 1.4 | Looking More at Correlations |
| 1.5 | Further Reading |
| Chapter 2 | More Than One IV – Multiple Regression |
| 2.1 | Introduction: Multiple Regression in Theory |
| 2.2 | Part I: What’s It All About? |
| 2.3 | Multiple Regression in Practice |
| 2.4 | R and R Square |
| 2.5 | Adjusted R Square |
| 2.6 | Analysis of Variance (ANOVA) Table |
| 2.7 | Coefficients |
| 2.8 | Variable Entry |
| 2.9 | Methods of Variable Entry |
| 2.10 | Further Reading |
| Chapter 3 | Categorical Independent Variables |
| This section of the web is incomplete. Sorry. |
Part II: I need to do regression analysis next week
| Chapter 4 | Assumptions In Regression Analysis |
| 4.1 | Introduction |
| 4.2 | Assumptions About Measures |
| 4.3 | Assumptions About Data |
| 4.4 | Univariate Distribution Checks |
| 4.5 | Calculation Based Methods |
| 4.6 | Dealing with Outliers, Skew and Kurtosis |
| 4.7 | Multivariate Distributions |
| 4.8 | Further Reading |
| Chapter 5 | Issues in Regression Analysis |
| 5.1 | Causality |
| 5.2 | Sample Size |
| 5.3 | Collinearity |
| 5.4 | Measurement Error |
| 5.5 | Further Reading |
Part III: I would like to know more of the things that regression analysis can do
| Chapter 6 | Nonlinear and Logistic Regression |
| 6.1 | |
| 6.2 | Nonlinear Regression |
| 6.2 | Logistic Regression |
| Chapter 7 | Moderator And Mediator Analysis |
| 7.1 | Nonlinear Regression |
| 7.1.1 | Linear and curvilinear relationships |
| 7.1.2 | Generating a Curve |
| 7.1.3 | Carrying Out Nonlinear Regression |
| 7.1.4 | An Example of Non-Linear Regression |
| 7.2 | Logistic Regression |
| 7.2.1 | The Case of the Dichotomous Dependent Variable |
| 7.2.2 | The Logit Transformation |
| 7.2.3 | Using the Logit: Logistic Regression |
| 7.2.4 | An Annotated Example of Logistic Regression |
| 7.2.5 | Hierarchical Logistic Regression |
| 7.2.6 | Polynomial Logistic Regression |
| 7.3 | Further reading |
| Chapter 8 | Introducing Some Advanced Techniques: Multilevel Modelling And Structural Equation Modelling. |
| 8.1 | Multilevel Modelling (MLM) |
| 8.1.1 | Why Use MLM |
| 8.1.2 | Algebraic Formulation |
| 8.1.3 | Hierarchies Everywhere |
| 8.2 | Structural Equation Modelling |
| 8.2.1 | Why use SEM |
| 8.2.2 | Identification |
| 8.2.3 | Latent Variables |
| 8.2.4 | Estimation in SEM |
| 8.2.5 | Model Testing |
| 8.2.6 | Some More Complex Models |
| 8.3 | Software for MLM and SEM |
| 8.4 | Further Reading |
| Appendix A | Equations used in regression |
| Appendix B | Using Computers to do regression |
| Appendix C | Tables of Critical Values |
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