Multilevel and Longitudinal Modelling
Full course description
Most datasets in European studies contain data whereby the traditional assumptions of ordinary least squares regression are violated, primarily in a cross-sectional and longitudinal context and because the dependent variable is non-continuous. Individuals are grouped into countries, (Eurobarometer surveys), European Union decision-making is recorded on an annual basis (EUPOL dataset), or members of the European Parliament are asked in how far they agree (five answer categories) with the statement that the European Parliament should have more powers with regard to a particular policy item (EPRG MEP Survey). This course aims to acquaint students with the most commonly used advanced statistical models to deal with clustered and (auto- or multi-) correlated data and categorical limited dependent variables.
One learns statistics best by applying the techniques to a substantive topic of interest. Students are asked to choose a dataset (with one or more of the ‘violations’ mentioned above) on a research topic related to the seminar that runs parallel to this course and they will work on this dataset from the first week onwards. Through the lectures and homework assignments, students will acquaint themselves with a method suitable for their research purposes which may include clustered and panel corrected standard errors, random and fixed effects models, multilevel models and logit, ordered logit and multinomial logit models. Students will be introduced to the assumptions underlying advanced statistical methods (hence students are not expected to be able to ‘do the math’ themselves); students learn to identify the data structure of a dataset and to recognize potential violations of traditional assumptions of ordinary least squares regression; students will choose an appropriate statistical model and apply it to commonly used datasets in European studies in a relevant statistical package (Stata). The course reserves ample of time to enable students to discuss with the group their progress of their final paper, from choosing a dataset to applying and interpreting the results of a statistical model. In this way, students will be able to write a paper which integrates substantive, theoretical with methodological knowledge and in which students show that they can clearly communicate the results produced by statistical modelling to other researchers within the multi- and interdisciplinary field of European Studies.
After this course students will be:
- Able to apply to statistical techniques suitable for (1) times-series-cross sectional data and/or (2) categorical and limited dependent variables and give appropriate statistical and substantive meaning to the results provided by these methods
- Able to integrate theories from the multi- and interdisciplinary field of European Studies with the statistical knowledge and methods discussed during this course and to clearly communicate these findings to other researchers within the multi- and interdisciplinary field of European Studies.
Cameron, A. Colin and Trivedi, Prain K. (2009) Microeconometrics Using Stata. College Station, Texas: Stata Press.