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Data Analysis Using Regression and Multilevel/Hierarchical Models

Authors

Andrew Gelman
, Columbia University, New York,
Jennifer Hill
, Columbia University, New York
Published 2006

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. 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…

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Key features

  • Discusses a wide range of linear and non-linear multilevel models
  • Provides R and Winbugs computer codes and contains notes on using SASS and STATA
  • Analyses illustrated with dozens of graphs of data and fitted models
  • Dozens of examples, almost all coming from Gelman/Hill's own applied research

About the book

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