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An Introduction to Multilevel Modeling Techniques

Second Edition

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This comprehensive, applied approach to multilevel analysis is distinguished by its wide range of applications relevant to the behavioral, educational, organizational, and social sciences. Univariate and multivariate models are used to understand how to design studies and analyze data. Readers are encouraged to consider what they are investigating, their data, and the strengths and limitations of each technique before selecting their approach. Numerous examples and exercises allow readers to test their understanding of the techniques. Input programs from HLM and Mplus demonstrate how to set up and run the models.

A latent variable conceptual framework is emphasized to show the commonality of the approaches and to make each technique more accessible. The first section is devoted to conceptual issues underlying multilevel modeling, while the second section develops several types of multilevel analyses including univariate regression, structural equation, growth curve and latent change, and latent variable mixture modeling. The new edition features:

  • New chapters on multilevel longitudinal and categorical models
  • 80% new exercises and examples
  • website at www.psypress.com/multilevel-modeling-techniques providing datasets and program setups in HLM, SPSS, Mplus, and LISREL
  • Increased emphasis on how multilevel techniques are used to examine changes in individuals and organizations over time.

Ideal for introductory graduate level courses on multilevel and/or latent variable modeling, this book is intended for students and researchers in psychology, business, education, health, and sociology interested in understanding multilevel modeling. Prerequisites include an introduction to data analysis and univariate statistics.

Table of Contents

Introduction 1. Investigating Organizational Structures, Processes, and Outcomes. 2. Development of Multilevel Modeling Techniques. 3. Multilevel Regression Models. 4. Defining Multilevel Latent Variables. 5. Multilevel Structural Equation Models. 6. Multilevel Longitudinal Analysis. 7. Multilevel Models with Categorical Variables. Afterword.

Reviews

"An insightful and authoritative textbook¦whether you are a newcomer to statistics or a long-time practitioner, this work is valuable both as a textbook and as a reference manual." -Terry E. Duncan, Oregon State University

"The new edition…offers an expanded introduction…By providing real data sets and completely updated computer examples analyzed with programs like HLM, LISREL, and Mplus, the book offers readers the latest information, steps, and procedures needed to competently conduct multilevel analyses." -George A. Marcoulides, University of California-Riverside

"Heck and Thomas provide an introduction to multilevel modeling that is not just comprehensive but also eminently readable. The authors’ broad coverage of techniques leaves the reader ready to investigate complex research questions using the latest advancements in multilevel analysis, including mixture and latent transition analyses." -Laura Stapleton, University of Maryland Baltimore County

Author Biography

Ronald H. Heck is professor of education at the University of Hawai‘i Manoa. His research focuses on organizational theory and quantitative research methods.

Scott L. Thomas is professor in the School of Educational Studies at Claremont Graduate University. His specialties include sociology of education, policy, and quantitative research methods.