Event history analysis : regression for longitudinal event data / Paul D. Allison.

Bibliography: p. 83-85.

1. Introduction -- Problems in the analysis of event histories -- An overview of event history methods -- 2. A discrete-time method -- A discrete-time example -- The discrete-time hazard rate -- A logit regression model -- Estimating the model -- Estimates for the biochemistry example -- The likelihood-ratio chi-square test -- Problems with the discrete-time method -- Discrete versus continuous time -- 3. Parametric methods for continuous-time data -- The continuous-time hazard rate -- Continuous-time regression models -- Maximum likelihood estimation -- An empirical example -- Censoring -- Some other models -- Choosing a model -- Unobserved sources of heterogeneity -- 4. Proportional hazards and partial likelihood -- The proportional hazards model -- Partial likelihood -- Time-varying explanatory variables -- Adequacy of the proportional hazards model -- Choice of origin of the time scale -- Partial likelihood for discrete-time data -- 5. Multiple kinds of events -- A classification of multiple kinds of events -- Estimation for multiple kinds of events -- Models for competing risks -- An empirical example of competing risks -- Dependence among different kinds of events -- 6. Repeated events -- A simple approach -- Problems with repeated events -- Extending the recidivism example -- Left censoring -- 7. Change of states -- Transition rates -- An analysis of job changes -- Simplifying the model -- 8. Conclusion.