Multilevel Modeling Using R

Author : W. Holmes Finch
Publisher : CRC Press
ISBN 13 : 1351062255
Total Pages : 242 pages
Book Rating : 4.51/5 ( download)

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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.

Author : W. Holmes Finch
Publisher : CRC Press
ISBN 13 : 1466515864
Total Pages : 225 pages
Book Rating : 4.64/5 ( download)

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Download or read book Multilevel Modeling Using R written by W. Holmes Finch and published by CRC Press. This book was released on 2016-03-09 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilevel Modelling using R provides 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. The book concludes with Bayesian fitting of multilevel models. Complete data sets for the book can be found on the book's website www.mlminr.com/

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

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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.

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

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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.

Author : Tom A. B. Snijders
Publisher : SAGE
ISBN 13 : 9780761958901
Total Pages : 282 pages
Book Rating : 4.08/5 ( download)

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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.

Author : Paul Roback
Publisher : CRC Press
ISBN 13 : 1439885400
Total Pages : 436 pages
Book Rating : 4.06/5 ( download)

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Download or read book Beyond Multiple Linear Regression written by Paul Roback and published by CRC Press. This book was released on 2021-01-14 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R is designed for undergraduate students who have successfully completed a multiple linear regression course, helping them develop an expanded modeling toolkit that includes non-normal responses and correlated structure. Even though there is no mathematical prerequisite, the authors still introduce fairly sophisticated topics such as likelihood theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. The case studies and exercises feature real data and real research questions; thus, most of the data in the textbook comes from collaborative research conducted by the authors and their students, or from student projects. Every chapter features a variety of conceptual exercises, guided exercises, and open-ended exercises using real data. After working through this material, students will develop an expanded toolkit and a greater appreciation for the wider world of data and statistical modeling. A solutions manual for all exercises is available to qualified instructors at the book’s website at www.routledge.com, and data sets and Rmd files for all case studies and exercises are available at the authors’ GitHub repo (https://github.com/proback/BeyondMLR)

Author : Karen Robson
Publisher : SAGE
ISBN 13 : 1473934303
Total Pages : 166 pages
Book Rating : 4.06/5 ( download)

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Download or read book Multilevel Modeling in Plain Language written by Karen Robson and published by SAGE. This book was released on 2015-11-02 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Have you been told you need to do multilevel modeling, but you can′t get past the forest of equations? Do you need the techniques explained with words and practical examples so they make sense? Help is here! This book unpacks these statistical techniques in easy-to-understand language with fully annotated examples using the statistical software Stata. The techniques are explained without reliance on equations and algebra so that new users will understand when to use these approaches and how they are really just special applications of ordinary regression. Using real life data, the authors show you how to model random intercept models and random coefficient models for cross-sectional data in a way that makes sense and can be retained and repeated. This book is the perfect answer for anyone who needs a clear, accessible introduction to multilevel modeling.

Author : Ita G G Kreft
Publisher : SAGE
ISBN 13 : 9781446230923
Total Pages : 164 pages
Book Rating : 4.29/5 ( download)

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Download or read book Introducing Multilevel Modeling written by Ita G G Kreft and published by SAGE. This book was released on 1998-04-07 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first accessible and practical guide to using multilevel models in social research. Multilevel approaches are becoming increasingly important in social, behavioural, and educational research and it is clear from recent developments that such models are seen as being more realistic, and potentially more revealing, than ordinary regression models. While other books describe these multilevel models in considerable detail none focuses on the practical issues and potential problems of doing multilevel analyses that are covered in Introducing Multilevel Modeling. The authors' approach is user-oriented and the formal mathematics and statistics are kept to a minimum. Other key features include the use of worked examples using real data sets, analyzed using the leading computer package for multilevel modeling - "MLn." Discussion site at: http: \www.stat.ucla.eduphplibw-agoraw-agora.phtml?bn=Sagebook Data files mentioned in the book are available from: http: \www.stat.ucla.edu deleeuwsagebook

Author : Joop J. Hox
Publisher : Routledge
ISBN 13 : 1317308689
Total Pages : 348 pages
Book Rating : 4.83/5 ( download)

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Download or read book Multilevel Analysis written by Joop J. Hox and published by Routledge. This book was released on 2017-09-14 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applauded for its clarity, this accessible introduction helps readers apply multilevel techniques to their research. The book also includes advanced extensions, making it useful as both an introduction for students and as a reference for researchers. Basic models and examples are discussed in nontechnical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines including psychology, education, public health, and sociology. Readers are introduced to a general framework on multilevel modeling which covers both observed and latent variables in the same model, while most other books focus on observed variables. In addition, Bayesian estimation is introduced and applied using accessible software.

Author : Ding-Geng (Din) Chen
Publisher : Springer Nature
ISBN 13 : 3030675831
Total Pages : 239 pages
Book Rating : 4.37/5 ( download)

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Download or read book Statistical Regression Modeling with R written by Ding-Geng (Din) Chen and published by Springer Nature. This book was released on 2021-04-08 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume is designed to guide the transition from classical to more advanced regression modeling, as well as to contribute to the rapid development of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling promotes the applications of R in linear, nonlinear, longitudinal and multi-level regression. All included datasets, as well as the associated R program in packages nlme and lme4 for multi-level regression, are detailed in Appendix A. This book will be valuable in graduate courses on applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related fields.