REVIEW OF JOOP J. HOX MULTILEVEL ANALYSIS – TECHNIQUES AND APPLICATIONS, Second Edition, Routledge (2010)

Multilevel Analysis - Techniques and Applications is intended as an introduction to multilevel analysis for students and applied researchers, a book that can be used either in psychology, education, sociology, or business courses. Hox takes the reader step by step into the area of multilevel data analysis, starting out with basic information and getting to more advanced and complex issues along the way. Most of the chapters on multilevel regression analysis should be readable for social scientists who have a good general knowledge of analysis of variance and classical multiple regression analysis. Some of these chapters contain material that is more difficult but this can be skipped at first reading (e.g. longitudinal models). The Multilevel Analysis is structured in sixteen main chapters and treats two classes of multilevel models: multilevel regression models, and multilevel models for covariance structures. In addition to the basic information, the reader becomes acquainted with some advanced modelling techniques that might be used, such as bootstrapping and Bayesian estimation methods. The applicability of the multilevel information is one of the strengths of this book: there are numerous examples and applications on various multilevel topics. The simpler examples are meant to help the novice. The basic models and examples are discussed in non-technical terms. The special applications, more complex examples combining more than one problem, can be useful to both researchers and methodologists.