Data Analysis Using Regression and Multilevel/Hierarchical Models Paperback / softback
by Andrew (Columbia University, New York) Gelman, Jennifer (Columbia University, New York) Hill
Part of the Analytical Methods for Social Research series
Paperback / softback
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 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.
Information
-
Only a few left - usually despatched within 24 hours
- Format:Paperback / softback
- Pages:648 pages, Worked examples or Exercises
- Publisher:Cambridge University Press
- Publication Date:18/12/2006
- Category:
- ISBN:9780521686891
Information
-
Only a few left - usually despatched within 24 hours
- Format:Paperback / softback
- Pages:648 pages, Worked examples or Exercises
- Publisher:Cambridge University Press
- Publication Date:18/12/2006
- Category:
- ISBN:9780521686891
