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Linear Mixed-Effects Models Using R

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Cover of 'Linear Mixed-Effects Models Using R'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Case Studies
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    Chapter 3 Data Exploration
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    Chapter 4 Linear Models with Homogeneous Variance
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    Chapter 5 Fitting Linear Models with Homogeneous Variance: The lm() and gls() Functions
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    Chapter 6 ARMD Trial: Linear Model with Homogeneous Variance
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    Chapter 7 Linear Models with Heterogeneous Variance
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    Chapter 8 Fitting Linear Models with Heterogeneous Variance: The gls() Function
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    Chapter 9 ARMD Trial: Linear Model with Heterogeneous Variance
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    Chapter 10 Linear Model with Fixed Effects and Correlated Errors
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    Chapter 11 Fitting Linear Models with Fixed Effects and Correlated Errors: The gls() Function
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    Chapter 12 ARMD Trial: Modeling Correlated Errors for Visual Acuity
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    Chapter 13 Linear Mixed-Effects Model
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    Chapter 14 Fitting Linear Mixed-Effects Models: The lme()Function
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    Chapter 15 Fitting Linear Mixed-Effects Models: The lmer() Function
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    Chapter 16 ARMD Trial: Modeling Visual Acuity
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    Chapter 17 PRT Trial: Modeling Muscle Fiber Specific-Force
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    Chapter 18 SII Project: Modeling Gains in Mathematics Achievement-Scores
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    Chapter 19 FCAT Study: Modeling Attainment-Target Scores
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    Chapter 20 Extensions of theRTools for Linear Mixed-Effects Models
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Title
Linear Mixed-Effects Models Using R
Published by
Springer Science & Business Media, February 2013
DOI 10.1007/978-1-4614-3900-4
ISBNs
978-1-4614-3899-1, 978-1-4614-3900-4, 978-1-4899-9667-1
Authors

Gałecki, Andrzej, Burzykowski, Tomasz, Andrzej Gałecki, Tomasz Burzykowski

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 10%
Professor 1 5%
Student > Bachelor 1 5%
Unknown 16 80%
Readers by discipline Count As %
Psychology 2 10%
Earth and Planetary Sciences 1 5%
Agricultural and Biological Sciences 1 5%
Unknown 16 80%