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Taking a practical, hands-on approach to multilevel modeling, this book provides readers with an accessible and concise introduction to HLM and how to use the technique to build models for hierarchical and longitudinal data. Each section of the book answers a basic question about multilevel modeling, such as, "How do you determine how well the model fits the data?" After reading this book, readers will understand research design issues associated with multilevel models, be able to accurately interpret the results of multilevel analyses, and build simple cross-sectional and longitudinal multilevel models.

Michael Lewis-Beck
Series Editor's Introduction
 
The Need for Multilevel Modeling
Theoretical reasons for multilevel models

 
Statistical reasons for multilevel models

 
Scope of Book

 
 
Basic Multilevel Modeling
The basic two-level multilevel model

 
How to build and evaluate a multilevel model

 
 
Extending the Basic Multilevel Model
Using generalized multilevel modeling

 
Three-level models

 
Longitudinal data as hierarchical: Time nested within person

 
 
Appendices
 
Datasets and other support materials
 
Software
 
Other Resources
 
References
 
About the Author
Key features
  • Numerous examples with real data help illustrate the concepts.
  • The text includes a list of resources for more advanced types of multilevel designs and analyses.
  • Sample data available on the author's website provide readers with a means to practice the concepts explained in the book.

Sample Materials & Chapters

Series Editor's Introduction

Chapter 1. The Need for Multilevel Modeling


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