Introduction to Multilevel Analysis
This course will teach you the theoretical basics of multilevel modeling and some important methodological and statistical issues. You will also learn how to analyze multilevel data sets with the HLM program, to interpret the output and to report the results. The benefits of multilevel analysis are discussed both in theory as with empirical examples.
This course restricts to a quantitative (i.e. continuous) outcome variable. Categorical outcomes are part of the course Advanced Multilevel.
Social research often involves problems that investigate the relationship between individual and society. The general concept is that individuals interact with the social contexts to which they belong, meaning that individual persons are influenced by the social groups or contexts to which they belong, and that the properties of those groups are in turn influenced by the individuals who make up that group.
Generally, the individuals and the social groups are conceptualized as a hierarchical system of individuals and groups, with individuals and groups defined at separate levels of this hierarchical system. The appropriate analysis technique for such a hierarchical system is multilevel analysis. The benefits of multilevel analysis are discussed both in theory as with empirical examples.
A good follow up is our Summer School course: 'Advanced Multilevel'
You might also be interested in:
- A gentle introduction to Bayesian Statistics, for if you have a small sample size
- Advanced Course on Using Mplus, for if you have intensive longitudinal data
A maximum of 25 participants will be allowed in this course.
Housing through Utrecht Summer School
Tuition fee for PhD students from the Faculty of Social and Behavioural Sciences from Utrecht University will be funded by the Graduate School of Social and Behavioural Sciences.