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

by Andrew Gelman

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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. 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.
  • ISBN13 9780511266836
  • Publish Date 25 March 2007 (first published 18 December 2006)
  • Publish Status Active
  • Publish Country GB
  • Publisher Cambridge University Press
  • Imprint Cambridge University Press (Virtual Publishing)
  • Format eBook
  • Language English