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Hierarchical Linear Models : Applications and Data Analysis Methods by Anthony S. Bryk, Stephen W. Raudenbush β€” book cover
Statistics, Social Sciences - Methodology, Mathematical Modeling - Science

Hierarchical Linear Models : Applications and Data Analysis Methods

by Anthony S. Bryk, Stephen W. Raudenbush
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Overview

Much social and behavioral research involves hierarchical data structures. The effects of school characteristics on students, how differences in government policies from country to country influence demographic relations within them, and how individuals exposed to different environmental conditions develop over time are a few examples. This introductory text explicates the theory and use of hierarchical linear models through rich illustrative examples and lucid explanations.

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Editorials

Journal of the American Statistical Association

"No other introductory text on hierarchial or multilevel models attempts to take the reader through a carefully structured set of examples, and so this book is certainly welcome. . . . I would recommend it to those who would like an introduction to the topic and a glimpse of some of the potential power of multilevel models."

Booknews

Launching a new Sage series, this introductory text explicates the theory and use of hierarchical linear models through clear explanations and illustrative examples. It describes use of both two and three level models in organizational research, studies of individual development and meta-analysis applications, and concludes with a formal derivation of the statistical methods used in the book. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Book Details

Published
April 10, 1992
Publisher
Sage Publications, Inc
Pages
265
Format
Hardcover
ISBN
9780803946279

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