Chapter
Event History Data Structures
Mathematical Components of Event History Analysis
Problems with Modeling Duration Data
CHAPTER 3 Parametric Models for Single-Spell Duration Data
Example 3.1: Weibull Model of U.N. Peacekeeping Missions
The Log-Logistic and Log-Normal Models
Example 3.2: Models of Candidacy Winnowing
Estimation of Parametric Models
Choosing among Parametric Distributions
Example 3.3: Generalized Gamma Model of Cabinet Duration
Example 3.4: The AIC and Models of Cabinet Duration
CHAPTER 4 The Cox Proportional Hazards Model
Problems with Parameterizing the Baseline Hazard
Example 4.1: A Cox Model of U.N. Peacekeeping Missions
The Exact Discrete Method
Example 4.2: Cox Models of Cabinet Durations
Interpretation of Cox Model Estimates
Retrieving the Baseline Hazard and Survivor Functions
Example 4.3: Baseline Functions and Cabinet Durations
CHAPTER 5 Models for Discrete Data
S(t), f(t), and h(t) for the Discrete-Time Model
Models for Discrete-Time Processes
Incorporating Duration in the Discrete-Time Framework
Temporal Dummy Variables and Transformations
Interpretation of Discrete-Time Model Estimates
Example 5.1: Discrete-Time Models of U.S. House Member Careers
Conditional Logit and the Cox Model
Example 5.2: Militarized Interventions
CHAPTER 6 Issues in Model Selection
Advantages and Disadvantages of Modeling Strategies
Parametric Models Revisited
Discrete-Time Models Revisited
Flexible Parametric Models
Example 6.1: Adoption of Restrictive Abortion Legislation
Do All Roads Lead to the Cox Model?
CHAPTER 7 Inclusion of Time-Varying Covariates
Incorporating Exogenous TVCs into the Duration Model
Counting Processes and Duration Data with TVCs
Example 7.1: Challenger Deterrence in U.S. House Elections
TVCs and Parametric Models
Example 7.2: Use of TVCs in a Weibull Model
TVCs and Discrete-Time Models
Example 7.3: House Careers and TVCs
Temporal Ordering of TVCs and Events
Temporal Dependence among Observations
Example 7.4: Robust Variance Estimation
CHAPTER 8 Diagnostic Methods for the Event History Model
Residuals in Event History Models
Residual Analysis and the Cox Model
Adequacy of the Cox Model
Example 8.1: Application Using Cox-Snell Residuals
Functional Form of a Covariate
Example 8.2: Application Using Martingale Residuals
Example 8.3: Influence Diagnostics Using Score Residuals
Poorly Predicted Observations
Example 8.4: Assessing Poorly Predicted Observations
The Adequacy of the Proportional Hazards Assumption
Example 8.5: Testing the PH Assumption
Residual Analysis and Parametric Models
Cox-Snell Residuals Applied to Parametric Models
Example 8.6: Using Cox-Snell Residuals to Assess Parametric Forms
Martingales, Deviance, and Score Residuals for Parametric Models
CHAPTER 9 Some Modeling Strategies for Unobserved Heterogeneity
Example 9.1: Use of Frailty Model with Conflict Data
The Split-Population Model
Example 9.2: Split Population Model of PAC Contributions
CHAPTER 10 Models for Multiple Events
Unordered Events of the Same Type
Variance-Corrected Models for Repeated Events
Example 10.1: A Repeated Events Model for Militarized Intervention Data
Frailty Models and Repeated Events Data
Latent Survivor Time Approach to Competing Risks
Example 10.2: Competing Risks Model of Congressional Careers
Multinomial Logit Approach to Competing Risks
Example 10.3: MNL Competing Risks Model of Congressional Careers
Stratified Cox Approach to Competing Risks
Example 10.4: State Adoption of Restrictive Abortion Legislation Using a Stratified Cox Model
CHAPTER 11 The Social Sciences and Event History
Common Problems in the Analysis of Social Science Event History Data
Failure to Discriminate among Event Types
Poor Measurement of Survival Times and TVCs
The Meaning of Time Dependency
What Should Social Scientists Do?
Connecting Theory to Events
When does the “clock start ticking?”
Which events are of interest?
What is the process of interest?
Are there different kinds of events that can occur?
Are TVCs going to be used in subsequent analyses?
Recommendations for Modeling Strategies
Is duration dependency a “nuisance”?
What issues emerge in the application of the Cox model?
In what settings might one use parametric methods?
What issues emerge in the application of parametric models?
What about discrete-time data?
What issues emerge in the application of “logit-type” models?
What about complicated event structures?
What about interpretation of event history results?
Appendix Software for Event History Analysis
Event History Modeling
：A Guide for Social Scientists
( Analytical Methods for Social Research )
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