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Linear mixed models. A practical guide using statistical software. With contributions from Brenda W. Gillespie. (English) Zbl 1269.62057

Boca Raton, FL: Chapman & Hall/CRC (ISBN 1-58488-480-0/hbk; 978-1-4200-1043-5/ebook). xix, 353 p. (2007).
Publisher’s description: Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), the book provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-navigate reference details the use of procedures for fitting LMMs in five popular statistical software packages: SAS, SPSS, Stata, R/S-plus, and HLM. The authors introduce basic theoretical concepts, present a heuristic approach to fitting LMMs based on both general and hierarchical model specifications, develop the model-building process step-by-step, and demonstrate the estimation, testing, and interpretation of fixed-effect parameters and covariance parameters associated with random effects. These concepts are illustrated through examples using real-world data sets that enable comparisons of model fitting options and results across the software procedures. The book also gives an overview of important options and features available in each procedure.

MSC:

62J05 Linear regression; mixed models
62-04 Software, source code, etc. for problems pertaining to statistics
62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics

Software:

R; HLM; WWGbook; MEMSS; SAS; SPSS; S-PLUS; Stata
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