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
- instructor: Brad Bushman
- instructor: Renate Dittrich
- instructor: Athanasia Pliakogianni
- instructor: Astrid Schütz
- instructor: Stefanie Singer
- instructor: Felicitas Meifert-Menhard
- instructor: Athanasia Pliakogianni
- instructor: Stefanie Singer
- instructor: Athanasia Pliakogianni
- instructor: Stefanie Singer
Introduction to the Legal Framework of Doctoral Studies and Good Academic Practice, Summer Term 2021
This course offers an overview on the various legal prerequisites of doctoral studies in the Free State of Bavaria. The participants of the course will be provided with detailed information on the legal procedure of doctoral studies based on the Bavarian University and College Act and the doctoral degree regulations of the faculties of the University. The course broaches as well the questions of academic fraud and plagiarism having arisen within the last few years as the basic principles of copyright law and good academic practice.
- instructor: Florian Kühhorn
- instructor: Athanasia Pliakogianni
- instructor: Stefanie Singer