Hierarchical and Multilevel Models
Partial pooling, shrinkage, and Bayesian model averaging.
Hierarchical and Multilevel Models. Partial pooling, shrinkage, and Bayesian model averaging.
Foundations and canonical references
The standard treatments of hierarchical and multilevel models approach the subject from complementary angles. Gelman, Data Analysis Using Regression and Multilevel/Hierarchical Models (2007) is the anchor reference for the subject and lays out the core definitions, theorems, and worked examples that practitioners return to.
Open methodological questions for hierarchical and multilevel models include sharpening the bridges between foundational theory and computational practice, extending classical results to broader or more structured settings, and integrating the techniques surveyed above with adjacent mathematical disciplines. The references listed in this page are the entry points that current work builds on.
Prerequisites
Sources
- textbook · primary · 2007Data Analysis Using Regression and Multilevel/Hierarchical Modelsgelman-2007, hill-2007
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