Description: Data Analysis Using Regression And Multilevel/Hierarchical Models, Hardcover by Gelman, Andrew; Hill, Jennifer, ISBN 0521867061, ISBN-13 9780521867061, Like New Used, Free shipping in the US 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. Th introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. Th 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:
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Book Title: Data Analysis Using Regression And Multilevel/Hierarchical Models
Number of Pages: 648 Pages
Language: English
Publication Name: Data Analysis Using Regression and Multilevel/Hierarchical Models
Publisher: Cambridge University Press
Publication Year: 2006
Item Height: 1.6 in
Subject: Probability & Statistics / Regression Analysis, Probability & Statistics / General
Item Weight: 47.3 Oz
Type: Textbook
Subject Area: Mathematics
Item Length: 10.3 in
Author: Jennifer Hill, Andrew Gelman
Series: Analytical Methods for Social Research Ser.
Item Width: 7.3 in
Format: Hardcover
