1.1 Causal Modeling and Observation Plans 1.2 Event History Analysis and Causal Modeling

2.1 Basic Terminology
2.2 Event History Data Organization

3.1 Life Table Method
3.2 Product-Limit Estimation
3.3 Comparing Survivor Functions

4.1 The Basic Exponential Model 4.2 Models with Multiple Decisions
4.3 Models with Multiple Episodes

5.1 The Basic Model
5.2 Models without Covariates
5.3 Models with Proportional Covariate Effects
5.4 Models with Period-Specific Effects

6.1 Parallel and Interdependent Processes
6.2 Interdependent Processes: The System Approach
6.3 Interdependent Processes: The Causal Approach
6.4 Episode Splitting with Qualitative Covariates
6.5 Episode Splitting with Quantitative Covariates
6.6 Application Examples

7.1 Interpretation of Time-Dependence
7.2 Gompertz Models
7.3 Weibull Models
7.4 Log-Logistic Models
7.5 Log-Normal Models

8.1 Simple Graphical Methods
8.2 Pseudoresiduals

9.1 Partial Likelihood Estimation
9.2 Time-Dependent Covariates
9.3 The Proportionality Assumption
9.4 Baseline Results and Survivor Functions
9.5 Application Example

10.1 Unobserved Heterogeneity
10.2 Models with a Mixture Distribution 10.3 Discussion