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Correlated Data Analysis: Modeling, Analytics, and Applications

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Correlated Data Analysis: Modeling, Analytics, and Applications
Springer New York

Table of Contents

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    Book Overview
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    Chapter 1 Introduction and Examples
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    Chapter 2 Dispersion Models
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    Chapter 3 Inference Functions
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    Chapter 4 Modeling Correlated Data
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    Chapter 5 Marginal Generalized Linear Models
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    Chapter 6 Vector Generalized Linear Models
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    Chapter 7 Mixed-Effects Models: Likelihood-Based Inference
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    Chapter 8 Mixed-Effects Models: Bayesian Inference
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    Chapter 9 Linear Predictors
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    Chapter 10 Generalized State Space Models
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    Chapter 11 Generalized State Space Models for Longitudinal Binomial Data
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    Chapter 12 Generalized State Space Models for Longitudinal Count Data
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    Chapter 13 Missing Data in Longitudinal Studies
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Title
Correlated Data Analysis: Modeling, Analytics, and Applications
Published by
Springer New York, January 2007
ISBNs
978-0-387-71393-9
Authors

Song, Peter X.-K

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