Event history, or duration analysis, is a method that is widely used across social science disciplines – particularly in sociology and political science, and also of interest in history, social policy, demography and economics. Beyond the practicalities of its statistical use, the method is essential for thinking about how social, political and economic processes evolve over time. I have used this method in my research in sociology, social policy, and political science, and the course will draw on interdisciplinary examples. Many important social science questions focus on time, duration, and the probability of event occurrence - the lengths of wars or legal disputes, the failure of cabinets over time, the longevity of alliances or dictatorships, the survival of firms or persons. Event history or survival analysis is a class of statistical techniques that analyzes the probability that an event occurs, how that probability changes over time, and how it is mediated by other factors. Event history analysis is a very coherent method, with a clear progression in how students acquire understanding. We start with the research logic of event history, data structure, nonparametric techniques, and introduction to multivariate survival models. The course will end with a discussion of special topics [competing risks, unobserved heterogeneity]. It is possible for students to master this method at an advanced level within an intensive one-week course. This course provides students with the key concepts and competence to pursue further statistical expertise of this method on their own.The course aims to introduce students to the key concepts of event history, data structure, an overview of parametric, semi-parametric and non-parametric approaches, and a focus on application of these concepts on practice datasets and students’ own data. Each class will consist of a lecture component where we will discuss key concepts, and an applied component where we will analyze data, and implement the concepts from the lecture. There will also be a time for lab-work in the afternoon, where students can work together on problem sets, with aid from the instructor. For more information : https://www.sciencespo.fr/ecole-doctorale/fr/actualites/event-history-analysis.html
- Sukriti ISSAR (Sciences Po)
Entry requirements: The course prerequisite is some experience with any statistical software (STATA, R), and that you have studied basic regression in some previous class.