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Publication year
Hierarchical linear models: Applications and data analysis methods
Resource type
Book
Authors/contributors
- Bryk, Anthony S. (Author)
- Raudenbush, Stephen W. (Author)
Title
Hierarchical linear models: Applications and data analysis methods
Abstract
Much social and behavioral research involves hierarchical data structures. . . . Recent developments in the statistical theory of hierarchical linear models now afford an integrated set of methods for such applications. This introductory text explicates the theory and use of hierarchical linear models (HLM) through rich, illustrative examples and lucid explanations. The presentation remains reasonably nontechnical by focusing on three general research purposes—improved estimation of effects within an individual unit, estimating and testing hypotheses about cross-level effects, and partitioning of variance and covariance components among levels. This innovative volume 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. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Series
Hierarchical linear models: Applications and data analysis methods
Place
Thousand Oaks, CA, US
Publisher
Sage Publications, Inc
Date
1992
# of Pages
xvi, 265
ISBN
978-0-8039-4627-9
Short Title
Hierarchical linear models
Library Catalogue
APA PsycNet
Extra
Pages: xvi, 265
Citation
Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models: Applications and data analysis methods. Sage Publications, Inc.
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