Show Summary Details

Page of

PRINTED FROM OXFORD HANDBOOKS ONLINE ( © Oxford University Press, 2018. All Rights Reserved. Under the terms of the licence agreement, an individual user may print out a PDF of a single chapter of a title in Oxford Handbooks Online for personal use (for details see Privacy Policy and Legal Notice).

date: 15 April 2021

Abstract and Keywords

Multilevel modeling in general concerns models for relationships between variables defined at different levels of a hierarchical data set, which is often viewed as a multistage sample from a hierarchically structured population. Common applications are individuals within groups, repeated measures within individuals, longitudinal modeling, and cluster randomized trials. This chapter treats the multilevel regression model, which is a direct extension of single-level multiple regression, and multilevel structural equation models, which includes multilevel path and factor analysis. Multilevel analysis was originally intended for continuous normally distributed data. This chapter refers to recent extensions to non-normal data but does not treat these in detail. The end of the chapter presents some statistical issues such as assumptions, sample sizes, and applications to data that are not completely nested.

Keywords: Multilevel model, mixed model, random coefficient, cluster sampling, hierarchical data

Access to the complete content on Oxford Handbooks Online requires a subscription or purchase. Public users are able to search the site and view the abstracts and keywords for each book and chapter without a subscription.

Please subscribe or login to access full text content.

If you have purchased a print title that contains an access token, please see the token for information about how to register your code.

For questions on access or troubleshooting, please check our FAQs, and if you can''t find the answer there, please contact us.