Aims of the course
This course gives students a practical grounding in the theory and methods of panel data analysis. It has the following key aims:
* To allow students to interpret and critically assess published studies using panel data
* To provide students with the skills and confidence to manipulate panel datasets on their own in the future
* To give an overview of different approaches to panel data analysis
* To develop practical skills in selecting and conducting different types of panel data analysis
* To provide an opportunity for students to compare results of analysing the same data with different panel methods
* The course includes a review of standard regression methods (OLS, logit and probit) and covers longitudinal data manipulation, transition matrices, continuous and discrete fixed and random effects models, and survival analysis.
- Module Supervisor: Silvia Avram
- Module Supervisor: Cara Booker
- Module Supervisor: Ayse Guveli