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Featuring a comprehensive, applied approach to multilevel analysis, this book is distinguished by its wide range of applications relevant to the behavioral, educational, organizational, and social sciences.
Both univariate and multivariate models are used to promote a greater understanding for designing studies and analyzing data. The text emphasizes how the conceptual and methodological approaches underpinning a study is an essential part of the research design. Readers are encouraged to consider the questions and theoretical orientation underlying their study, the structure of the data, and the strengths and limitations of each technique before selecting their approach.
Numerous examples of cross-sectional and longitudinal data are provided along with related exercises. Examples of input programs from HLM (Version 6) and Mplus (Version 4) demonstrate how to set up and run the models. A website with datasets and program setups in HLM, Mplus, and Lisrel (version 8) for the book's examples and exercises is provided. Readers can also use MLwin, Stata, and SAS to conduct most of the analyses in the book.
The text emphasizes a latent variable conceptual framework for exploring hierarchical data. This framework allows the authors to show the commonality of the various approaches to multilevel modeling.
Part I is devoted to conceptual issues while the remainder of the book features increasingly popular multilevel techniques including the univariate multilevel model, the multilevel measurement model, multilevel structural equation models, longitudinal multilevel models, and continuous and categorical latent variable mixture models.
Introducing a systematic approach to the conceptual issues at the beginning of the book, helps to make each technique covered in Part II more accessible. Conceptual and computational problems at the end of each chapter allow readers to test their understanding of the techniques.
The new edition features:
- New chapters on multilevel longitudinal analysis and on multilevel models.
- 80% new exercises and examples.
- A book specific website with datasets and program setups in HLM, Mplus, and Lisrel.
- A greater emphasis on demonstrating how multilevel modeling 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 fields such as psychology, business, education, health, and sociology interested in understanding the advantages (and pitfalls) of multilevel modeling. Prerequisites include an introduction to data analysis and first-year univariate statistics.