300250 Soziologische Methoden - quantitativ: Regression Models for Hierarchical Data (S) (SoSe 2023)

Many questions in the social sciences are best answered with data that have a hierarchical structure, i.e., data available at different levels. For example, to investigate whether differences between countries are systematically related to individual attitudes, information is needed at the individual level (attitudes) and at the country level (operationalization of country differences). Similarly, a hierarchical data structure is needed to study the consequences of life course changes at the individual level. In this case, the additional level besides the individual is the temporal level. While data in which individuals are nested in different contexts - such as individuals in countries - are usually analyzed with so-called multilevel models, panel models are usually applied for changes in individual life courses. In cases where individuals are observed in different contexts over time, hybrid forms of the two types of models are also used.

The seminar will first discuss in which cases a "normal" regression model is not the best method for answering research questions and what advantages multilevel and panel models offer in comparison. The mathematical and statistical foundations of each of these model types will be explained and practical exercises will be conducted using teaching data sets. Emphasis is placed on practical applications and the differences and similarities among the model types.

Requirements for participation, required level

Students should have a good understanding of linear regression analysis in order to participate adequately in the course. However, lack of prior knowledge can be compensated by self-study during the first weeks. The practical exercises will be carried out with the help of guided exercise sheets. Appropriate knowledge of the syntax in "Stata" is helpful in order to be able to participate adequately in the practical exercises. In principle, the exercises can also be completed using "R", but the solutions for the exercise sheets will be provided and discussed as "Stata" syntax.