Multilevel Modeling Using R, 3rd Edition
“Multilevel Modeling Using R, Third Edition,” authored by W. Holmes Finch and Jocelyn E. Bolin, serves as a comprehensive guide for conducting multilevel data modeling within the R software environment. The book begins with a review of standard linear models before introducing the fundamentals of multilevel models and their implementation in R. It further explores the application of multilevel modeling to longitudinal data and highlights R’s graphical capabilities. Additionally, the text addresses models for categorical dependent variables in both single-level and multilevel contexts.
This third edition introduces several new topics absent from previous versions. Notably, it includes a chapter dedicated to fitting multilevel latent variable models in R, encompassing factor analysis, structural models, item response theory, and latent class models. Moreover, new sections discuss alternatives to standard multilevel models, such as fixed effects models and generalized estimating equations, which are particularly beneficial for small samples and when modeling correlation structures within higher-level units like schools. The edition also features a section on mediation modeling in the multilevel context.
This thoroughly updated revision provides readers with state-of-the-art tools to embark on their own investigations into multilevel modeling and gain deeper insights into their research endeavors.
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