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Mixed-Effects Models in S and S-PLUS de José Pinheiro

Mixed-Effects Models in S and S-PLUS: Statistics and Computing

Autor José Pinheiro, Douglas Bates
en Limba Engleză Paperback – 21 mar 2013
“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)
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Specificații

ISBN-13: 9781475781441
ISBN-10: 147578144X
Pagini: 548
Ilustrații: XVI, 528 p.
Dimensiuni: 155 x 235 x 29 mm
Greutate: 0.76 kg
Ediția:Softcover reprint of the original 1st ed. 2000
Editura: Springer
Colecția Springer
Seria Statistics and Computing

Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

Linear Mixed-Effects Models.- Linear Mixed-Effects Models: Basic Concepts and Examples.- Theory and Computational Methods for Linear Mixed-Effects Models.- Describing the Structure of Grouped Data.- Fitting Linear Mixed-Effects Models.- Extending the Basic Linear Mixed-Effects Model.- Nonlinear Mixed-Effects Models.- Nonlinear Mixed-effects Models: Basic Concepts and Motivating Examples.- Theory and Computational Methods for Nonlinear Mixed-Effects Models.- Fitting Nonlinear Mixed-Effects Models.

Recenzii

“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)

Caracteristici

This book provides an overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data.