Handbook of regression analysis

Part I. The multiple linear regression model

1. Multiple linear regression

2. Model building

Part II. Addressing violations of assumptions

3. Diagnostics for unusual observations

4. Transformations and linearizable models

5. Time series data and autocorrelation

Part III. Categorical predictors

6. Analysis of variance

7. Analysis of covariance

Part IV. Other regression models

8. Logistic regression

9. Multinomial regression

10. Count regression

11. Nonlinear regression.