Linear Mixed Models

Linear Mixed Models
Author: Brady T. West
Publisher: CRC Press
Total Pages: 376
Release: 2006-11-22
Genre: Mathematics
ISBN: 1420010433


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Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-nav


Linear Mixed Models
Language: en
Pages: 376
Authors: Brady T. West
Categories: Mathematics
Type: BOOK - Published: 2006-11-22 - Publisher: CRC Press

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Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Soft
Linear Mixed Models
Language: en
Pages: 442
Authors: Brady T. West
Categories: Mathematics
Type: BOOK - Published: 2014-07-17 - Publisher: CRC Press

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Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM
Linear Mixed-Effects Models Using R
Language: en
Pages: 558
Authors: Andrzej GaƂecki
Categories: Mathematics
Type: BOOK - Published: 2013-02-05 - Publisher: Springer Science & Business Media

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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
Linear and Generalized Linear Mixed Models and Their Applications
Language: en
Pages: 269
Authors: Jiming Jiang
Categories: Mathematics
Type: BOOK - Published: 2007-05-30 - Publisher: Springer Science & Business Media

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This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. It presents an up-to-date account of theory
Generalized Linear Mixed Models
Language: en
Pages: 547
Authors: Walter W. Stroup
Categories: Mathematics
Type: BOOK - Published: 2016-04-19 - Publisher: CRC Press

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With numerous examples using SAS PROC GLIMMIX, this text presents an introduction to linear modeling using the generalized linear mixed model as an overarching