Summer School in Statistics 2014 - Multilevel Modeling

Many kinds of data used in analysis and estimation have a hierarchical structure, where data observations can be clustered at one or several levels. For instance, an employee is hired at a department, at a local unit of an enterprise; or a pupil is in a class, at a school within a school district. Failing to take hierarchical data structures into account in the analysis and estimation may result in invalid inferences. This summer school gives an introduction to multilevel modeling, which provides tools for addressing hierarchical data structures.