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Data Analysis Using Regression and Multilevel/Hierarchical Models
Data Analysis Using Regression and Multilevel/Hierarchical Models

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Manufacturer: Cambridge University Press
Publisher: Cambridge University Press
Author(s): Andrew Gelman, Jennifer Hill

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Product Description:
Binding: Paperback
Brand: imusti
EAN: 9780521686891
Edition: 1
Feature: Cambridge University Press
ISBN: 052168689X
Item Dimensions: Array
Label: Cambridge University Press
Languages: Array
Manufacturer: Cambridge University Press
MPN: 22754172
Number Of Items: 1
Number Of Pages: 648
Publication Date: 2006-12-18
Publisher: Cambridge University Press
Studio: Cambridge University Press
Product Features:
Cambridge University Press
Editorial Review:
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. Author resource page: http://www.stat.columbia.edu/~gelman/arm/
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