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A glossary for multilevel analysis.

A V Diez Roux¹

¹Division of General Medicine, 622 West 168th Street, PH 9 East Rm 105, New York, NY 10032, USA. ad290@columbia.edu

Journal of Epidemiology and Community Health

|July 16, 2002

Summary

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Multilevel analysis is a statistical technique valuable in public health and epidemiology. This glossary explains its key concepts and terms for better understanding.

Area of Science:

Statistics
Epidemiology
Public Health

Background:

Multilevel analysis is an increasingly important statistical technique.
It is widely applied in fields such as public health and epidemiology.

Purpose of the Study:

To define key concepts and terms used in multilevel analysis.
To provide a glossary for researchers and practitioners.

Main Methods:

This work is a glossary, not an empirical study.
It defines fundamental terms related to multilevel modeling.

Main Results:

Key concepts such as fixed and random effects are defined.
Common terminology in multilevel analysis is clarified.

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Conclusions:

Understanding multilevel analysis terminology is crucial for its effective application.
This glossary serves as a resource for navigating the complexities of multilevel modeling.