The workshop covers basic and advanced methods of panel data analysis for social research from an applied perspective. The focus is on individual data from panel surveys (large N, small T).
Panel data offer important advantages over cross-sectional data, in particular, the identification of causal effects with relatively weak assumptions and the analysis of individual life-course trajectories. Special methods for panel data analysis are however needed to make use of these advantages. The workshop gives an applied overview. The starting point is the linear fixed effects (FE) regression model and its advantages compared to alternative models (random effects). The course furthermore covers the modelling of impact functions and growth curves with practical advice for researchers. Finally, useful extensions will be presented, notably the linear FE model with Individual Slopes (FEIS) and the FE logistic regression model (FE Logit). In the workshop, the structure of regression models is explained. The application of statistical models is demonstrated with Stata and real data examples.
Panel data offer important advantages over cross-sectional data, in particular, the identification of causal effects with relatively weak assumptions and the analysis of individual life-course trajectories. Special methods for panel data analysis are however needed to make use of these advantages. The workshop gives an applied overview. The starting point is the linear fixed effects (FE) regression model and its advantages compared to alternative models (random effects). The course furthermore covers the modelling of impact functions and growth curves with practical advice for researchers. Finally, useful extensions will be presented, notably the linear FE model with Individual Slopes (FEIS) and the FE logistic regression model (FE Logit). In the workshop, the structure of regression models is explained. The application of statistical models is demonstrated with Stata and real data examples.
- instructor: Courses Bamberg Graduate School of Social Sciences
- instructor: Athanasia Pliakogianni
- instructor: Stefanie Singer