Description
Luke (community health, Saint Louis University) examines single-equation, regression-style, two- or three-level modeling, using the example of pro-tobacco voting by members of Congress as a function of individual-level and aggregate characteristics, and discusses goodness-of-fit measures including the Akaike and Bayesian information criteria. He looks at two popular software packages, HLM and R/S-Plus, and provides tables and discussion of more specialized programs, including SAS and SPSS. There is no subject index. Annotation ©2004 Book News, Inc., Portland, OR (booknews.com)
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Taking a practical, hands-on approach to multilevel modeling, this book provides readers with an accessible and concise introduction to HLM and how to use the technique to build models for hierarchical and longitudinal data. Each section of the book answers a basic question about multilevel modeling, such as, "How do you determine how well the model fits the data?" After reading this book, readers will understand research design issues associated with multilevel models, be able to accurately interpret the results of multilevel analyses, and build simple cross-sectional and longitudinal multilevel models.
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