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Handbook of Advanced Multilevel Analysis

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Part of the European Association for Methodology Series series

This practical introduction helps readers apply multilevel techniques to their research. Noted as an accessible introduction, the book also includes advanced extensions making it useful as both an introduction and as a reference to students, researchers, and methodologists. Basic models and examples are discussed in non-technical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines. For example, readers will find data sets on stress in hospitals, GPA scores, survey responses, street safety, epilepsy, divorce, and sociometric scores, to name a few. The data sets are available on the website in SPSS, HLM, MLwiN, LISREL and/or Mplus files. Readers are introduced to both the multilevel regression model and multilevel structural models.

Highlights of the second edition include:

Two new chapters --one on Multilevel Models for Ordinal and Count Data (Ch. 7) and another on Multilevel Survival Analysis (Ch. 8).

Thoroughly unpdated chapters on multilevel structural equation modeling that reflect the enormous technical progress of the last few years.

The addition of some simpler examples to help the novice, but the more complex examples that combine more than one problem were retained.

A new section on multivariate meta-analysis (Ch. 11).

Expanded discussions of covariance structures across time and analyzing longitudinal data where no trend is expected.

Expanded chapter on Logistic Model for Dichotomous Data and Proportions with new estimation methods.

An updated website at www.joophox.net/ with data sets for all the text examples and up to date screen shots and PowerPoint slides for Instructors.

Ideal for introductory courses on multilevel modeling and/or ones that introduce this topic in some detail taught in a variety of disciplines including psychology, education, sociology, the health sciences, and business, the advanced extensions also make this a favorite resource for researchers and methodologists in these disciplines. A basic understanding of ANOVA and multiple regression is assumed. The section on multilevel structural equation models assumes a basic understanding of SEM.

Table of Contents

Part 1: Introduction　 J. Hox, J. K. Roberts, Multilevel Analysis: Where We Were and Where We Are.　 Part 2: Multilevel Latent Variable Modeling (LVM)　 B, Muthén, T. Asparouhov, Beyond Multilevel Regression Modeling: Multilevel Analysis in a General Latent Variable Framework.　 A. Kamata, B. Vaughn, Multilevel IRT Modeling.　 J. Vermunt, Mixture Models for Multilevel Data Sets.　 Part 3: Multilevel Models for Longitudinal Data　 J. Hox, Panel Modeling: Random Coefficients and Covariance Structures.　 R. D. Stoel, F. G. Garre, Growth Curve Analysis using Multilevel Regression and Structural Equation Modeling. 　Part 4: Special Estimation Problems D. Hedeker, R. J. Mermelstein, Multilevel Analysis of Ordinal Outcomes Related to Survival Data.　 E. L. Hamaker, I. Klugkist, Bayesian Estimation of Multilevel Models.　 H. Goldstein, Bootstrapping in Multilevel Models.　 S. van Buuren, Multiple Imputation of Multilevel Data.　 J. Kim, C. M. Swoboda, Handling Omitted Variable Bias in Multilevel Models: Model Specification Tests and Robust Estimation.　 J. K. Roberts, J. P. Monaco, H. Stovall, V. Foster, Explained Variance in Multilevel Models.　 E. L. Hamaker, P. van Hattum, R. M. Kuiper, H. Hoijtink, Model Selection Based on Information Criteria in Multilevel Modeling.　 M. Moerbeek, S. Teerenstra, Optimal Design in Multilevel Experiments.　 Part 5: Specific Statistical Issues　 J. Algina, H. Swaminathan, Centering in Two-Level Nested Designs. S. N. Beretvas, Cross-Classified and Multiple Membership Models.　 D. A. Kenny, D. A. Kashy, Dyadic Data Analysis using Multilevel Modeling.

Reviews

"Dr. Hox is a master at presenting sophisticated statistical ideas and models in very pragmatic way… There have been many developments in the area of multilevel structural equation modeling and [Hox’s] book is the only multilevel one that covers this important area…The additional chapters … make the book more … appealing … I would definitely use Hox’s book… [and] recommend it to my colleagues." - Donald Hedeker, University of Illinois at Chicago, USA

"The second edition offers a simplistic yet in-depth coverage of difficult material. It follows closely the style and approach of the highly successful first edition. The [book] also incorporates many of the latest developments that have emerged over the past few years in the field." - George A. Marcoulides, University of California, Riverside, Quantitative Methodology Series Editor

"This book continues to be one of the most readable texts on multilevel analysis. Hox does a masterful job of making the complex palatable. This book is a great addition for the practitioner and methodologist alike." - J. Kyle Roberts, Southern Methodist University, USA

"The writing style is unquestionably a strength of this book particularly when compared to competing books…. Without question I would adopt the revised version and recommend it to others. The … changes … strengthen an already effective book." - Dick Carpenter, University of Colorado, Colorado Springs, USA

Author Biography

Joop J. Hox is Professor and Chair of Social Science Methodology at Utrecht University. A Fellow of the Royal Statistical Society and a founding member of the European Association of Methodology, his recent publications focus on survey non-response, interviewer effects, survey data quality, missing data, and multilevel analysis of regression and structural equation models. He is the author of Multilevel Analysis (Routledge) and a co-editor of the International Handbook of Survey Methodology (Routledge).

J. Kyle Roberts is an associate professor of Teaching and Learning at Southern Methodist University in Dallas, Texas. Dr. Roberts has conducted numerous training sessions on multilevel analysis at annual meetings of the American Psychological Association, the American Educational Research Association, and the Southwest Educational Research Association. He has authored several book chapters and articles on multilevel analysis, and currently works with school districts in the development of value-added models for student and teacher accountability. He earned his Ph.D. in Educational Psychology from Texas A&M University.