Data Analysis Using Regression And Multilevel Hierarchical Models

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Data Analysis Using Regression And Multilevel Hierarchical Models
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Author : Andrew Gelman
language : en
Publisher: Cambridge University Press
Release Date : 2007
Data Analysis Using Regression And Multilevel Hierarchical Models written by Andrew Gelman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematics categories.
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 : Andrew Gelman
language : en
Publisher: Cambridge University Press
Release Date : 2006-12-18
Data Analysis Using Regression And Multilevel Hierarchical Models written by Andrew Gelman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-18 with Mathematics categories.
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 : Andrew Gelman
language : en
Publisher:
Release Date : 2009
Data Analysis Using Regression And Multilevel Hierarchical Models written by Andrew Gelman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
Regression And Other Stories
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Author : Andrew Gelman
language : en
Publisher: Cambridge University Press
Release Date : 2020-07-23
Regression And Other Stories written by Andrew Gelman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-23 with Mathematics categories.
Most textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression. It is about using regression to solve real problems of comparison, estimation, prediction, and causal inference. Unlike other books, it focuses on practical issues such as sample size and missing data and a wide range of goals and techniques. It jumps right in to methods and computer code you can use immediately. Real examples, real stories from the authors' experience demonstrate what regression can do and its limitations, with practical advice for understanding assumptions and implementing methods for experiments and observational studies. They make a smooth transition to logistic regression and GLM. The emphasis is on computation in R and Stan rather than derivations, with code available online. Graphics and presentation aid understanding of the models and model fitting.
Teaching Statistics
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Author : Andrew Gelman
language : en
Publisher: OUP Oxford
Release Date : 2002-08-08
Teaching Statistics written by Andrew Gelman and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-08-08 with Mathematics categories.
Students in the sciences, economics, psychology, social sciences, and medicine take introductory statistics. Statistics is increasingly offered at the high school level as well. However, statistics can be notoriously difficult to teach as it is seen by many students as difficult and boring, if not irrelevant to their subject of choice. To help dispel these misconceptions, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, examples and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and combines chapters such as, 'First week of class', with exercises to break the ice and get students talking; then 'Descriptive statistics' , collecting and displaying data; then follows the traditional topics - linear regression, data collection, probability and inference. Part II gives tips on what does and what doesn't work in class: how to set up effective demonstrations and examples, how to encourage students to participate in class and work effectively in group projects. A sample course plan is provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics and sampling.
Bayesian Data Analysis Third Edition
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Author : Andrew Gelman
language : en
Publisher: CRC Press
Release Date : 2013-11-01
Bayesian Data Analysis Third Edition written by Andrew Gelman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-01 with Mathematics categories.
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.
Hierarchical Linear Modeling
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Author : G. David Garson
language : en
Publisher: SAGE
Release Date : 2013
Hierarchical Linear Modeling written by G. David Garson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Mathematics categories.
This book provides a brief, easy-to-read guide to implementing hierarchical linear modeling using three leading software platforms, followed by a set of original how-to applications articles following a standardard instructional format. The "guide" portion consists of five chapters by the editor, providing an overview of HLM, discussion of methodological assumptions, and parallel worked model examples in SPSS, SAS, and HLM software. The "applications" portion consists of ten contributions in which authors provide step by step presentations of how HLM is implemented and reported for introductory to intermediate applications.
Multilevel Analysis
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Author : Tom A. B. Snijders
language : en
Publisher: SAGE
Release Date : 1999
Multilevel Analysis written by Tom A. B. Snijders and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Mathematics categories.
Multilevel analysis covers all the main methods, techniques and issues for carrying out multilevel modeling and analysis. The approach is applied, and less mathematical than many other textbooks.
Data Analysis
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Author : Charles M. Judd
language : en
Publisher:
Release Date : 2017
Data Analysis written by Charles M. Judd and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Mathematical statistics categories.
Noted for its model-comparison approach and unified framework based on the general linear model (GLM), this classic text provides readers with a greater understanding of a variety of statistical procedures including analysis of variance (ANOVA) and regression.