Data Analysis Using Regression and Multilevel/Hierarchical Models

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Publisher : Cambridge University Press
ISBN 13 : 9780521686891
Total Pages : 654 pages
Book Rating : 4.9X/5 ( download)

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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 and published by Cambridge University Press. This book was released on 2007 with total page 654 pages. 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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Publisher : Cambridge University Press
ISBN 13 : 1139460935
Total Pages : 7 pages
Book Rating : 4.34/5 ( download)

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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 and published by Cambridge University Press. This book was released on 2006-12-18 with total page 7 pages. 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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Publisher :
ISBN 13 :
Total Pages : 625 pages
Book Rating : 4.56/5 ( download)

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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 and published by . This book was released on 2009 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Regression and Other Stories

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Publisher : Cambridge University Press
ISBN 13 : 110702398X
Total Pages : 551 pages
Book Rating : 4.87/5 ( download)

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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 and published by Cambridge University Press. This book was released on 2020-07-23 with total page 551 pages. 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.

Hierarchical Linear Models

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Publisher : SAGE Publications, Incorporated
ISBN 13 :
Total Pages : 296 pages
Book Rating : 4.78/5 ( download)

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Book Synopsis Hierarchical Linear Models by : Anthony S. Bryk

Download or read book Hierarchical Linear Models written by Anthony S. Bryk and published by SAGE Publications, Incorporated. This book was released on 1992 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hierarchical Linear Models launches a new Sage series, Advanced Quantitative Techniques in the Social Sciences. This introductory text explicates the theory and use of hierarchical linear models (HLM) through rich, illustrative examples and lucid explanations. The presentation remains reasonably nontechnical by focusing on three general research purposes - improved estimation of effects within an individual unit, estimating and testing hypotheses about cross-level effects, and partitioning of variance and covariance components among levels. This innovative volume describes use of both two and three level models in organizational research, studies of individual development and meta-analysis applications, and concludes with a formal derivation of the statistical methods used in the book.

Bayesian Data Analysis, Third Edition

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Publisher : CRC Press
ISBN 13 : 1439840954
Total Pages : 677 pages
Book Rating : 4.55/5 ( download)

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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 and published by CRC Press. This book was released on 2013-11-01 with total page 677 pages. 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.

Teaching Statistics

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Publisher : OUP Oxford
ISBN 13 : 0191606995
Total Pages : 353 pages
Book Rating : 4.91/5 ( download)

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Book Synopsis Teaching Statistics by : Andrew Gelman

Download or read book Teaching Statistics written by Andrew Gelman and published by OUP Oxford. This book was released on 2002-08-08 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Multilevel Analysis

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Publisher : SAGE
ISBN 13 : 9780761958901
Total Pages : 282 pages
Book Rating : 4.08/5 ( download)

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Book Synopsis Multilevel Analysis by : Tom A. B. Snijders

Download or read book Multilevel Analysis written by Tom A. B. Snijders and published by SAGE. This book was released on 1999 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Multilevel Modeling Using R

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Publisher : CRC Press
ISBN 13 : 1351062255
Total Pages : 242 pages
Book Rating : 4.51/5 ( download)

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Book Synopsis Multilevel Modeling Using R by : W. Holmes Finch

Download or read book Multilevel Modeling Using R written by W. Holmes Finch and published by CRC Press. This book was released on 2019-07-16 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Like its bestselling predecessor, Multilevel Modeling Using R, Second Edition provides the reader with a helpful guide to conducting multilevel data modeling using the R software environment. After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data. New in the Second Edition: Features the use of lmer (instead of lme) and including the most up to date approaches for obtaining confidence intervals for the model parameters. Discusses measures of R2 (the squared multiple correlation coefficient) and overall model fit. Adds a chapter on nonparametric and robust approaches to estimating multilevel models, including rank based, heavy tailed distributions, and the multilevel lasso. Includes a new chapter on multivariate multilevel models. Presents new sections on micro-macro models and multilevel generalized additive models. This thoroughly updated revision gives the reader state-of-the-art tools to launch their own investigations in multilevel modeling and gain insight into their research. About the Authors: W. Holmes Finch is the George and Frances Ball Distinguished Professor of Educational Psychology at Ball State University. Jocelyn E. Bolin is a Professor in the Department of Educational Psychology at Ball State University. Ken Kelley is the Edward F. Sorin Society Professor of IT, Analytics and Operations and the Associate Dean for Faculty and Research for the Mendoza College of Business at the University of Notre Dame.

Categorical Data Analysis and Multilevel Modeling Using R

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Publisher : SAGE Publications
ISBN 13 : 154432491X
Total Pages : 745 pages
Book Rating : 4.13/5 ( download)

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Book Synopsis Categorical Data Analysis and Multilevel Modeling Using R by : Xing Liu

Download or read book Categorical Data Analysis and Multilevel Modeling Using R written by Xing Liu and published by SAGE Publications. This book was released on 2022-02-24 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: Categorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal, nominal, and count response variables using the R software. Author Xing Liu offers a unified framework for both single-level and multilevel modeling of categorical and count response variables with both frequentist and Bayesian approaches. Each chapter demonstrates how to conduct the analysis using R, how to interpret the models, and how to present the results for publication. A companion website for this book contains datasets and R commands used in the book for students, and solutions for the end-of-chapter exercises on the instructor site.