Chapter 1. Introduction
Chapter 2. Regression Models for A Dichotomous Dependent Variable
Chapter 3. Interpreting And Comparing Effects Within One Equation
Chapter 4. Comparing Subgroups Or Time Points: Investigating Interaction Effects
Chapter 5. Causal Modeling: Estimating Total, Direct, Indirect And Spurious Effects; Using Effect Coefficients From Different (Nested) Equations
Chapter 6. Concluding Remarks; Extensions, Effect Measures And Evaluation

Interpreting and Comparing Effects in Logistic, Probit and Logit Regression shows applied researchers how to compare coefficient estimates from regression models for categorical dependent variables in typical research situations. It presents a practical, unified treatment of these problems, and considers the advantages and disadvantages of each approach, and when to use them.