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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

Datasets and other support materials
Other Resources
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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