lecturer Dr. Carl Berning, Universität Mainz
target group: Participants are expected to be familiar with inferential statistics and basic regression models.
language: English
content:
This workshop gives an applied introduction to multilevel regression analysis. This methodology accounts for nested or so-called hierarchical data structures, e.g., voters nested within constituencies, pupils in classes/schools, or managers in organizations. In this workshop, participants will learn to examine relationships between variables measured on different levels of analysis, as well as, disentangle and interpret different variance components. Beyond the conceptual understanding, participants will learn how to apply this methodology in Stata. Multilevel regressions are advanced statistical models and therefore, participants are expected to be familiar with inferential statistics and basic regression models.
literature:
- Joop J. Hox, Mirjam Moerbeek, Rens van de Schoot (2018). Multilevel analysis. Techniques and applications. 3rd Edition. New York: Routledge.
- Snijders, Tom A.B., and Bosker, Roel J. (2012) Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling, second edition, London etc.: Sage Publishers.
course requirements (2 credits):
t. b. a.