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:
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.
"The book describes extensive knowledge of multilevel analysis of experiments. The author presents a very detailed description of multivariate techniques, shows examples where these methods can be used, and gives the interpretation of results. … This volume is a guide book of multilevel methods for the researchers who want to understand and use the multilevel techniques in practice. It is written in a clear and accessible manner." - Anna Szczepa´nska, Pozna´n University of Life Sciences, Poland, in International Statistical Review
"Dr. Hox is a master at presenting sophisticated statistical ideas and models in very pragmatic ways… 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 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
1. Introduction to Multilevel Analysis. 2. The Basic Two-Level Regression Model. 3. Estimation and Hypothesis Testing in Multilevel Regression. 4. Some Important Methodological and Statistical Issues. 5. Analyzing Longitudinal Data. 6. The Multilevel Generalized Linear Model for Dichotomous Data and Proportions. 7. The Multilevel Generalized Linear Model for Categorical and Count Data. 8. Multilevel Survival Analysis. 9. Cross-classified Multilevel Models. 10. Multivariate Multilevel Regression Models. 11. The Multilevel Approach to Meta-Analysis. 12. Sample Sizes and Power Analysis in Multilevel Regression. 13. Advanced Issues in Estimation and Testing. 14. Multilevel Factor Models. 15. Multilevel Path Models. 16. Latent Curve Models.
This series presents methodological techniques for investigators and students.
Each volume focuses on a specific method with the goal of providing an understanding and working knowledge of each method with a minimum of mathematical derivations.