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Data Analysis Using Regression and Multilevel/Hierarchical Models

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Release : 2007
Genre : Mathematics
Kind : eBook
Book Rating : 891/5 ( reviews)

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Book Synopsis Data Analysis Using Regression and Multilevel/Hierarchical Models by : Andrew Gelman

Download or read book Data Analysis Using Regression and Multilevel/Hierarchical Models written by Andrew Gelman. This book was released on 2007. Available in PDF, EPUB and Kindle. Book excerpt: This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

Data Analysis Using Regression and Multilevel/Hierarchical Models

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Author :
Release : 2006-12-18
Genre : Mathematics
Kind : eBook
Book Rating : 935/5 ( reviews)

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Book Synopsis Data Analysis Using Regression and Multilevel/Hierarchical Models by : Andrew Gelman

Download or read book Data Analysis Using Regression and Multilevel/Hierarchical Models written by Andrew Gelman. This book was released on 2006-12-18. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Data Analysis Using Regression and Multilevel/hierarchical Models

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Author :
Release : 2009
Genre :
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Data Analysis Using Regression and Multilevel/hierarchical Models by : Andrew Gelman

Download or read book Data Analysis Using Regression and Multilevel/hierarchical Models written by Andrew Gelman. This book was released on 2009. Available in PDF, EPUB and Kindle. Book excerpt:

Regression and Other Stories

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Release : 2020-07-23
Genre : Business & Economics
Kind : eBook
Book Rating : 98X/5 ( reviews)

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Book Synopsis Regression and Other Stories by : Andrew Gelman

Download or read book Regression and Other Stories written by Andrew Gelman. This book was released on 2020-07-23. Available in PDF, EPUB and Kindle. Book excerpt: A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference.

Bayesian Data Analysis, Third Edition

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Author :
Release : 2013-11-01
Genre : Mathematics
Kind : eBook
Book Rating : 954/5 ( reviews)

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Book Synopsis Bayesian Data Analysis, Third Edition by : Andrew Gelman

Download or read book Bayesian Data Analysis, Third Edition written by Andrew Gelman. This book was released on 2013-11-01. Available in PDF, EPUB and Kindle. Book excerpt: Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

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