Search Results

Linear Mixed-Effects Models Using R

Download or Read eBook Linear Mixed-Effects Models Using R PDF written by Andrzej Gałecki and published by Springer Science & Business Media. This book was released on 2013-02-05 with total page 558 pages. Available in PDF, EPUB and Kindle.
Linear Mixed-Effects Models Using R
Author :
Publisher : Springer Science & Business Media
Total Pages : 558
Release :
ISBN-10 : 9781461439004
ISBN-13 : 1461439000
Rating : 4/5 (04 Downloads)

Book Synopsis Linear Mixed-Effects Models Using R by : Andrzej Gałecki

Book excerpt: Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics, educational measurement, and sociology. This book aims to support a wide range of uses for the models by applied researchers in those and other fields by providing state-of-the-art descriptions of the implementation of LMMs in R. To help readers to get familiar with the features of the models and the details of carrying them out in R, the book includes a review of the most important theoretical concepts of the models. The presentation connects theory, software and applications. It is built up incrementally, starting with a summary of the concepts underlying simpler classes of linear models like the classical regression model, and carrying them forward to LMMs. A similar step-by-step approach is used to describe the R tools for LMMs. All the classes of linear models presented in the book are illustrated using real-life data. The book also introduces several novel R tools for LMMs, including new class of variance-covariance structure for random-effects, methods for influence diagnostics and for power calculations. They are included into an R package that should assist the readers in applying these and other methods presented in this text.


Linear Mixed-Effects Models Using R Related Books

Linear Mixed-Effects Models Using R
Language: en
Pages: 558
Authors: Andrzej Gałecki
Categories: Mathematics
Type: BOOK - Published: 2013-02-05 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a vari
Mixed Effects Models and Extensions in Ecology with R
Language: en
Pages: 579
Authors: Alain Zuur
Categories: Science
Type: BOOK - Published: 2009-03-05 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

This book discusses advanced statistical methods that can be used to analyse ecological data. Most environmental collected data are measured repeatedly over tim
Mixed-Effects Models in S and S-PLUS
Language: en
Pages: 538
Authors: José C. Pinheiro
Categories: Computers
Type: BOOK - Published: 2009-04-15 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

R, linear models, random, fixed, data, analysis, fit.
Multivariate Generalized Linear Mixed Models Using R
Language: en
Pages: 284
Authors: Damon Mark Berridge
Categories: Mathematics
Type: BOOK - Published: 2011-04-25 - Publisher: CRC Press

DOWNLOAD EBOOK

Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling reade
Linear Models with R
Language: en
Pages: 284
Authors: Julian J. Faraway
Categories: Mathematics
Type: BOOK - Published: 2016-04-19 - Publisher: CRC Press

DOWNLOAD EBOOK

A Hands-On Way to Learning Data AnalysisPart of the core of statistics, linear models are used to make predictions and explain the relationship between the resp
Scroll to top