Data analysis using regression and multilevel/hierarchical models
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Author
Contributions
- Hill, Jennifer, 1969- - Contributor
Publication
2007 - Cambridge University Press, Cambridge, England
Language
English
Word Count
156,250 words, Guess
Page Count
625 pages
Identifiers
- Open LibraryOL17931187M
- ISBN-139780521867061
- ISBN-100521867061
- OCLC Control Number67375137
- OCLC Control Numberdataanalysisusin00gelm_997
and 3 more
- Library of Congress Control Number2006040566
- LibraryThing1526203
- Goodreads737071
Classifications
- DDC519.5/36
- LCCHA31.3 .G45 2007
Description
"Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout."--Publisher description.
Subjects
Topics
Series Statement
- Analytical methods for social research
Other Editions
- Data analysis using regression and multilevel/hierarchical models
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