Please register in advance (email to instructor) as the number of participants is limited.
Does marriage increase happiness? Does poverty alter an individual's party affiliation? Does further education pay off in higher earnings? To answer such questions, it is necessary to have data with ... read more
Does marriage increase happiness? Does poverty alter an individual's party affiliation? Does further education pay off in higher earnings? To answer such questions, it is necessary to have data with repeated measures and to analyze these data with longitudinal data analysis techniques. This course offers an introduction to the analysis of quantitative longitudinal data. The course will start out with a short recap of ordinary least square regression analysis, with regression diagnostics, and with the specific nature of longitudinal data. The main part of class is devoted to a selection of the most relevant analytical models for longitudinal data: fixed-effect, random-effect, and hybrid models for both, linear and categorical dependent variables; sequence analysis; and event data analysis.
The seminar is set up as an intensive workshop on four days in October. It will include lectures introducing to the new modeling techniques as well as computer lab sessions, in which students will apply these techniques with Stata and learn how to interpret the empirical results. This course wants to attract students in sociology (3rd semester M.A. and higher) and students from neighboring departments and institutes who are well familiar with linear regression models. It is especially interesting for students who might consider an empirical quantitative M.A. thesis with longitudinal data.
Rabe-Hesketh, Sophia and Anders Skrondal (2011): Multilevel and Longitudinal Modeling Using Stata; College Station: Stata Press