This course is an introduction to theory and applications of event-history analysis, plus some elements of panel data analysis. Longitudinal data are commonly used to address many research questions in demography, social sciences, and epidemiology.
- Blossfeld, H., K. Golsch, and G. Rohwer. 2007. Event History Analysis with Stata. Mahwah, NJ: Lawrence Erlbaum.
- Scherer, S. 2013. Analisi dei dati longitudinali. Un'introduzione pratica. Bologna: Il Mulino.
- Slides and additional materials will be provided during the course.
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.
Face-to-face lessons and lab sessions.
Type of Assessment
Written exam that icludes both exercises in Stata and questions on theory.
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); Introduction to panel data and related regression models (random and fixed effects).