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Hierarchical model

As explained in Effective Data Analysis

A hierarchical model represents data whose observations are nested within groups and estimates patterns at multiple levels.

A hierarchical model represents observations nested within groups, such as students within classrooms, schools, and states. It extends regression and classification models to estimate patterns at multiple levels. section 9.1.1 section 9.4

Hierarchical models help answer questions involving both individuals and the groups they belong to:

  • Compare subcontractor performance while accounting for relationships with primary contracting companies. section 9.1.1
  • Estimate expected tenure for employees hired across different departments. section 9.1.1
  • Model student test performance using individual, classroom, school, and state-level factors. section 9.1.1

The approach is especially useful for complex real-world phenomena involving people in their everyday environments, including nonprofit and public-sector settings. It can support stakeholder questions and peer-reviewed research. section 9.1.1

How Effective Data Analysis covers it

How deep it goes
Defines the model class and illustrates its levels, but stops short of explaining estimation procedures or implementation details.
Examples
Uses subcontractors, employee departments, and students nested within classrooms, schools, and states.
What it assumes
Assumes familiarity with regression or classification and recognizes groups such as classrooms, schools, districts, or departments.
What you can do after
Evaluate/understand when nested data require patterns to be modeled at both individual and group levels.
How it connects
Connects hierarchical models with regression, classification, nested groups, and model evaluation.

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This explainer was generated by Manning's knowledge graph from the text of Effective Data Analysis. The section links point to the parts of the book it draws on.