Introduction to Generalized Linear Modelling - Federico Vegetti

The aim of this course is to offer a detailed but accessible introduction to generalized linear modelling (GLM). Political scientists are often confronted with outcome variables that are not linear, such as e.g. survey respondents' choices among two or more options, which require different types of non-linear transformations in order to be estimated. GLM is a common technique used to obtain meaningful results in these cases. Thus, the aim of the course is to make students comfortable with applying GLM techniques to a variety of outcome variables. The course contains an introduction to the logic of GLM and maximum likelihood estimation, logit models for binary, ordered and multinomial dependent variables, as well as models for count data. Short Bio Federico Vegetti is a post-doc researcher in political science at the Central European University in Budapest. He took his PhD in political science from the University of Mannheim in 2013. His research interests include political psychology, public opinion formation and voting, comparative political behaviour and quantitative research methodology.

---