Data Analysis Using Regression and Multilevel/Hierarchical Models (Hardcover) (ISBN-13: 9780521867061)

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/

Author: Andrew Gelman, Jennifer Hill
ISBN-10: 0521867061
ISBN-13: 9780521867061
Publisher: Cambridge University Press
Language: English
Published: 12/25/2006
Pages: 648
Format: Hardcover
Weight: 2.95lbs
Size: 10.20h x 7.20w x 1.60d