36-663 Multilevel and Hierarchical Models

9 units, Carnegie Mellon University

Multilevel and hierarchical models are among the most broadly applied sophisticated statistical models, especially in the social and biological sciences. They apply to situations in which the data cluster naturally into groups of units that are more related to each other than they are the rest of the data.In the first part of the course we will see how to generalize linear models to multilevel and hierarchical models and relate them to other areas of statistics, and in the last part of the course we will learn how Bayesian statistical methods can help us to build, estimate and diagnose problems with these models using a variety of data sets and examples.

Prerequisites: none listed

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