Data Analysis Using Regression and Multilevel/Hierarchical Models 1st Edition

4.2 out of 5 stars 76 ratings
ISBN-13: 978-0521686891
ISBN-10: 052168689X
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Frequently bought together

  • Data Analysis Using Regression and Multilevel/Hierarchical Models
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Editorial Reviews

Review

"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 written what may be the first truly modern book on modeling. Containing practical as well as methodological insights into both Bayesian and traditional approaches, Data Analysis Using Regression and Multilevel/Hierarchical Models provides useful guidance into the process of building and evaluating models. For the social scientist and other applied statisticians interested in linear and logistic regression, causal inference, and hierarchical models, it should prove invaluable either as a classroom text or as an addition to the research bookshelf."
Richard De Veaux, Williams College

"The theme of Gelman and Hill's engaging and nontechnical introduction to statistical modeling is 'Be flexible.' Using a broad array of examples written in R and WinBugs, the authors illustrate the many ways in which readers can build more flexibility into their predictive and causal models. This hands-on textbook is sure to become a popular choice in applied regression courses."
Donald Green, Yale University

"Simply put, Data Analysis Using Regression and Multilevel/Hierarchical Models is the best place to learn how to do serious empirical research. Gelman and Hill have written a much needed book that is sophisticated about research design without being technical. Data Analysis Using Regression and Multilevel/Hierarchical Models is destined to be a classic!"
Alex Tabarrok, George Mason University

"a detailed, carefully written exposition of the modelling challenge, using numerous convincing examples, and always paying careful attention to the practical aspects of modeling. I recommend it very warmly."
Journal of Applied Statistics

"Gelman and Hill's book is an excellent intermediate text that would be very useful for researchers interested in multilevel modeling... This book gives a wealth of information for anyone interested in multilevel modeling and seems destined to be a classic."
Brandon K. Vaughn, Journal of Eductional Measurement

"With their new book, Data Analysis Using Regression and Multilevel/Hierarchical Models, Drs. Gelman and Hill have raised the bar for what a book on applied statistical modeling should seek to accomplish. The book is extraordinarily broad in scope, modern in its approach and philosophy, and ambitious in its goals... I am tremendously impressed with this book and highly recommend it. Data Analysis Using Regression and Multilevel/Hierarchical Models deserves to be widely read by applied statisticians and practicing researchers, especially in the social sciences. Instructors considering textbooks for courses on the practice of statistical modeling should move this book to the top of their list."
Daniel B. Hall, Journal of the American Statistical Association

"Data Analysis Using Regression and Multilevel/Hierarchical Models is the book I wish I had in graduate school."
Timothy Hellwig, The Political Methodologist

Book Description

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 and demonstrates a wide variety of models and instructs the reader in how to fit these models using freely available software packages.

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Customer reviews

4.2 out of 5 stars
4.2 out of 5
76 customer ratings
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Reviewed in the United States on April 10, 2018
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Reviewed in the United States on May 28, 2014
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Reviewed in the United States on December 19, 2013
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Reviewed in the United States on July 22, 2014
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Top international reviews

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5.0 out of 5 stars Another classic from Gelman
Reviewed in the United Kingdom on December 29, 2007
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Alberto G B
4.0 out of 5 stars Good to start but some bad things
Reviewed in Spain on May 9, 2020
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Nicolas Corneau-Tremblay
4.0 out of 5 stars Cover a lot of material in a clear and accessible ...
Reviewed in Canada on October 24, 2017
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Jose Maria Lahoz
5.0 out of 5 stars Comprehensible and very didactic
Reviewed in Spain on December 30, 2012
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muffin
5.0 out of 5 stars Libro completo, ottimo!
Reviewed in Italy on February 20, 2013
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HELDER MATEUS VIANA
5.0 out of 5 stars Very Good.
Reviewed in Canada on November 24, 2013
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Murilo
5.0 out of 5 stars excelent book
Reviewed in France on July 1, 2013
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Mike M
5.0 out of 5 stars excellent book
Reviewed in Germany on December 31, 2013
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Richard Tol
2.0 out of 5 stars Statistics is not a bag of tricks
Reviewed in the United Kingdom on September 16, 2015
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