Blossfeld, H., K. Golsch, and G. Rohwer. 2007. Event History Analysis with Stata. Mahwah, NJ: Lawrence Erlbaum.
This course covers univariate and multivariate (regression) methods for analysis of duration (event-history) data, including their recent developments. Students also learn data management skills that are specific to conducting event-history analysis in Stata.
Throughout the course students will apply event-history techniques to own research projects.
Type of Assessment
Written exam that icludes both exercises in STATA and questions on theory.
For attending students, the mark of the written exam will be cumulated with the result of a mini-project conducted at home and presented in class. The mark of that mini-project ranges from 0 to 4.
Introduction (Basic concepts and definitions, Event history data, censoring and truncation, discrete vs. continuous time); Event history data (Coding and data preparation, Life tables, Kaplan-Meier, related estimators, Stata applications, time-constant and time-varying variables); Non-parametric models (Exponential and piece-wise constant models); Modelling-related issues (Interactions and combinations of variables; model choice and goodness of fit); Parametric models (Weibull, Gompertz, Log-Logistic, Log-Normal); Cox model (Estimation, interpretation of parameters and model diagnostics, PH assumption); Competing risk models (Data preparation, estimation and interpretation); Advanced topics (Discrete time models, frailty models – unobserved heterogeneity, multiprocess and multilevel extensions of event history models)