Data Analysis Using Regression and Multilevel/Hierarchical Models
Andrew Gelman; Jennifer Hill
ISBN 10: 052168689X ISBN 13: 9780521686891
Published by Cambridge University Press, 2006
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A nearly new copy with no defects, just a slight bump to the upper spine, hence a 'damaged' stamp to one of the preliminary pages. Despite such this book looks and feels unread with contents that are crisp, fresh and tight. Thus a very nice book in great condition, now offered for sale at a reasonable price. Seller Inventory # 135354
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.
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Bibliographic Details
Title: Data Analysis Using Regression and ...
Publisher: Cambridge University Press
Publication Date: 2006
Binding: Paperback
Condition: Like New
Edition: First Edition.
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Data Analysis Using Regression and Multilevel/Hierarchical Models
Published by
Cambridge University Press, 2006
ISBN 10: 052168689X
ISBN 13: 9780521686891
Used
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First Edition
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paperback. Condition: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. Ships same or next business day. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes). Seller Inventory # 000854440U
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Data Analysis Using Regression and Multilevel/Hierarchical Models
Published by
Cambridge University Press, 2006
ISBN 10: 052168689X
ISBN 13: 9780521686891
New
paperback
First Edition
Seller: Textbooks_Source, Columbia, MO, U.S.A.
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paperback. Condition: New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes). Seller Inventory # 000854440N
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Data Analysis Using Regression and Multilevel/Hierarchical Models (Paperback)
Published by
Cambridge University Press, Cambridge, 2006
ISBN 10: 052168689X
ISBN 13: 9780521686891
New
Paperback
First Edition
Seller: CitiRetail, Stevenage, United Kingdom
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Paperback. Condition: new. Paperback. 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: / gelman/arm/ 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: ~gelman/arm/ Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780521686891
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Data Analysis Using Regression and Multilevel/Hierarchical Models
Published by
Cambridge University Press, 2006
ISBN 10: 052168689X
ISBN 13: 9780521686891
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First Edition
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Condition: New. 2006. 1st Edition. 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. . . . . . Seller Inventory # V9780521686891
Quantity: 2 available
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Data Analysis Using Regression and Multilevel/Hierarchical Models (Paperback)
Published by
Cambridge University Press, Cambridge, 2006
ISBN 10: 052168689X
ISBN 13: 9780521686891
New
Paperback
First Edition
Seller: Grand Eagle Retail, Fairfield, OH, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. 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: / gelman/arm/ 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: ~gelman/arm/ Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521686891
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Data Analysis Using Regression and Multilevel/Hierarchical Models
Published by
Cambridge University Press, 2006
ISBN 10: 052168689X
ISBN 13: 9780521686891
New
Paperback
First Edition
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Paperback. Condition: New. 1st Edition. Special order direct from the distributor. Seller Inventory # ING9780521686891
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Data Analysis Using Regression and Multilevel/Hierarchical Models (Paperback)
Published by
Cambridge University Press, Cambridge, 2006
ISBN 10: 052168689X
ISBN 13: 9780521686891
New
Paperback
First Edition
Seller: AussieBookSeller, Truganina, VIC, Australia
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Paperback. Condition: new. Paperback. 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: / gelman/arm/ 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: ~gelman/arm/ Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9780521686891
Quantity: 1 available