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Data Analysis Using Regression and Multilevel/Hierarchical Models
Andrew Gelman
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Description for Data Analysis Using Regression and Multilevel/Hierarchical Models
paperback. This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models. Series Editor(s): Alvarez, R. Michael; Beck, Nathaniel L.; Wu, Lawrence L. Series: Analytical Methods for Social Research. Num Pages: 648 pages, 160 exercises. BIC Classification: JHBC; PBK. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 254 x 179 x 37. Weight in Grams: 1120. Series: Analytical Methods for Social Research. 648 pages, 160 exercises. For the applied researcher performing data analysis using linear and nonlinear regression and multilevel models. Cateogry: (P) Professional & Vocational; (U) Tertiary Education (US: College). BIC Classification: JHBC; PBK. Dimension: 254 x 179 x 37. Weight: 1132. Series Editor(s) :Alvarez, R. Michael; Beck, Nathaniel L.; Wu, Lawrence L.
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 ... Read more
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 ... Read more
Product Details
Publisher
Cambridge University Press
Number of pages
648
Format
Paperback
Publication date
2006
Series
Analytical Methods for Social Research
Condition
New
Weight
1147g
Number of Pages
648
Place of Publication
Cambridge, United Kingdom
ISBN
9780521686891
SKU
V9780521686891
Shipping Time
Usually ships in 4 to 8 working days
Ref
99-3
About Andrew Gelman
Andrew Gelman is Professor of Statistics and Professor of Political Science at Columbia University. He has published over 150 articles in statistical theory, methods, and computation, and in applications areas including decision analysis, survey sampling, political science, public health, and policy. His other books are Bayesian Data Analysis (1995, second edition 2003) and Teaching Statistics: A Bag of Tricks ... Read more
Reviews for Data Analysis Using Regression and Multilevel/Hierarchical Models
'Data Analysis Using Regression and Multilevel/Hierarchical Models' … careful yet mathematically accessible style is generously illustrated with examples and graphical displays, making it ideal for either classroom use or self-study. It appears destined to adorn the shelves of a great many applied statisticians and social scientists for years to come.' Brad Carlin, University of Minnesota 'Gelman and Hill have ... Read more