Data Analysis Using Regression and Multilevel / Hierarchical Models (Analytical Methods for Social Research)

Andrew Gelman/ Jennifer Hill

ISBN 10: 0521867061 / ISBN 13: 9780521867061

Published by Cambridge Univ Pr, 2007

About this Item

1st edition. 625 pages. 10.25x7.25x1.50 inches. In Stock. Seller Inventory # x-0521867061

Bibliographic Details

Title: Data Analysis Using Regression and ...

Publisher: Cambridge Univ Pr

Publication Date: 2007

Binding: Hardcover

Condition: Brand New

About this title

Synopsis:

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/

Book Description:

Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. It introduces and demonstrates a variety of models and instructs the reader in how to fit these models using freely available software packages.