Modeling Binary Correlated Responses using SAS, SPSS and R

Part I. Introduction and Review of Modeling Uncorrelated Observations

1. Introduction to Binary Logistic Regression
Jeffrey R. Wilson, Kent A. Lorenz

2. Short History of the Logistic Regression Model
Jeffrey R. Wilson, Kent A. Lorenz

3. Standard Binary Logistic Regression Model
Jeffrey R. Wilson, Kent A. Lorenz

Part II. Analyzing Correlated Data Through Random Component

4. Overdispersed Logistic Regression Model
Jeffrey R. Wilson, Kent A. Lorenz

5. Weighted Logistic Regression Model
Jeffrey R. Wilson, Kent A. Lorenz

6. Generalized Estimating Equations Logistic Regression
Jeffrey R. Wilson, Kent A. Lorenz

7. Generalized Method of Moments Logistic Regression Model
Jeffrey R. Wilson, Kent A. Lorenz

8. Exact Logistic Regression Model
Jeffrey R. Wilson, Kent A. Lorenz

Part III. Analyzing Correlated Data Through Systematic Components

9. Two-Level Nested Logistic Regression Model
Jeffrey R. Wilson, Kent A. Lorenz

10. Hierarchical Logistic Regression Models
Jeffrey R. Wilson, Kent A. Lorenz

11. Fixed Effects Logistic Regression Model
Jeffrey R. Wilson, Kent A. Lorenz

Part IV. Analyzing Correlated Data Through the Joint Modeling of Mean and Variance

12. Heteroscedastic Logistic Regression Model
Jeffrey R. Wilson, Kent A. Lorenz

Keywords: Statistics, Statistical Theory and Methods, Biostatistics, Statistics for Life Sciences, Medicine, Health Sciences