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[Shiny App] Hierarchical Models

[Shiny App] Hierarchical Models

Hierarchical models are used when there is nesting of observational units in the data and variables are observed on multiple levels of the hierarchy. Failure to account for the hierarchy in the data may result in invalid conclusions. However, hierarchical models are not always needed for nested data as the intraclass correlation coefficient determines the requirement. This app focuses on illustrating the concept of hierarchical models by comparing the method to the two others at the extremes: the pooled and unpooled methods. Users are shown mathematically and visually how the hierarchical estimates are weighted averages and how they serve as a balance between the pooled and unpooled estimates; the two related ideas of shrinkage and borrowing strength are illustrated in this process. Users... Show More
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