Mixed-Effects Models in S and S-Plus

ISBN-13: 9781475781441 / Angielski / Miękka / 2013 / 528 str.

Jose Pinheiro; Douglas Bates

Opis

Mixed-e?ects models provide a ?exibleand powerful toolfor theanalysis of grouped data, which arise in many areas as diverse as agriculture, biology, economics, manufacturing, and geophysics. Examples of grouped data - clude longitudinal data, repeatedmeasures, blocked designs, and multilevel data. The increasing popularity of mixed-e?ects models is explained by the ?exibility they o?er in modeling the within-group correlation often present in grouped data, by the handling of balanced and unbalanced data in a uni?ed framework, and by the availability of reliable and e?cient software for ?tting them. This book provides an overview of the theory and application of l- ear and nonlinear mixed-e?ects models in the analysis of grouped data. A uni?ed model-building strategy for both linear and nonlinear models is presentedandappliedtotheanalysisofover20realdatasetsfromawide- riety of areas, including pharmacokinetics, agriculture, and manufacturing. A strong emphasis is placed on the use of graphical displays at the various phases of the model-building process, starting with exploratory plots of the data and concluding withdiagnostic plots toassess the adequacy ofa ?tted model. Over 170 ?gures are included in the book.

Recenzje

"Over 170 figures are included in the book. ... the material covered in the book is self-contained ... . The balanced mix of real data examples, modeling software, and theory makes this book a useful reference for practitioners who use, or intend to use, mixed-effects models in their data analyses. It can also be used as a text for a one-semester graduate-level applied course in mixed-effects models." (E.M.Psyadlo, zbMATH 0953.62065, 2022)

Spis treści

Linear Mixed-Effects * Theory and Computational Methods for LME Models * Structure of Grouped Data * Fitting LME Models * Extending the Basic LME Model * Nonlinear Mixed-Effects * Theory and Computational Methods for NLME Models * Fitting NLME Models

O autorze

Mixed Effects Models involve measurements made over time on an
individual in an experiment. This book presents the most recent
techniques for analyzing this type of data in the statistical software
program S-PLUS. It will be of interest to researchers and graduate
students in statistics, biostatistics, and epidemiology.