Linear Mixed Models
Author: Brady T. West (Author), Kathleen B. Welch (Author), Andrzej T Galecki (Author) & 0 more
Edition 版本: 3rd
Publication Date 出版日期: 2022-06-24
Language 语言: English
Print Length 页数: 490 pages
ISBN-10: 1032019328
ISBN-13: 9781032019321
Book Description
Highly recommended by JASA, Technometrics, and other leading statistical journals, the first two editions of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Third Edition continues to lead readers step-by-step through the process of fitting LMMs.
The third edition provides a comprehensive update of the available tools for fitting linear mixed-effects models in the newest versions of SAS, SPSS, R, Stata, and HLM. All examples have been updated, with a focus on new tools for visualization of results and interpretation. New conceptual and theoretical developments in mixed-effects modeling have been included, and there is a new chapter on power analysis for mixed-effects models.
Features:•Dedicates an entire chapter to the key theories underlying LMMs for clustered, longitudinal, and repeated measures data
•Provides descriptions, explanations, and examples of software code necessary to fit LMMs in SAS, SPSS, R, Stata, and HLM
•Contains detailed tables of estimates and results, allowing for easy comparisons across software procedures
•Presents step-by-step analyses of real-world data sets that arise from a variety of research settings and study designs, including hypothesis testing, interpretation of results, and model diagnostics
•Integrates software code in each chapter to compare the relative advantages and disadvantages of each package
•Supplemented by a website with software code, datasets, additional documents, and updates
Ideal for anyone who uses software for statistical modeling, this book eliminates the need to read multiple software-specific texts by covering the most popular software programs for fitting LMMs in one handy guide. The authors illustrate the models and methods through real-world examples that enable comparisons of model-fitting options and results across the software procedures.
Review
“. . . this book is perfect for readers who are looking for a quick reference to all kinds of situations in which LMMs are to be used. In the opinion of the reviewer, either this book or the Gałecki and Burzykowski (2013) book are a must for the practical statistician working with R. And the reviewer finds it helpful to have both on the shelf. For readers with a great need to incorporate novel data visualization approaches in their analyses and the need to improve result interpretation, the third edition is clearly superior to the second edition.”
~ Andreas Ziegler, Biometrics Journal
“This book will definitively help researchers and statisticians reach a deeper understanding of linear mixed models and provides them with the resources to perform a proper analysis whatever their statistical software of choice.”
~ Célia Touraine, ISCB Book Reviews
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