Table of Contents

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   Book Overview
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   Chapter 1 Introduction
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   Chapter 2 Examples
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   Chapter 3 A Model for Longitudinal Data
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   Chapter 4 Exploratory Data Analysis
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   Chapter 5 Estimation of the Marginal Model
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   Chapter 6 Inference for the Marginal Model
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   Chapter 7 Inference for the Random Effects
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   Chapter 8 Fitting Linear Mixed Models with SAS
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    Chapter 9 General Guidelines for Model Building
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    Chapter 10 Exploring Serial Correlation
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    Chapter 11 Local Influence for the Linear Mixed Model
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    Chapter 12 The Heterogeneity Model
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    Chapter 13 Conditional Linear Mixed Models
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    Chapter 14 Exploring Incomplete Data
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    Chapter 15 Joint Modeling of Measurements and Missingness
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    Chapter 16 Simple Missing Data Methods
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    Chapter 17 Selection Models
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    Chapter 18 Pattern-Mixture Models
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    Chapter 19 Sensitivity Analysis for Selection Models
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    Chapter 20 Sensitivity Analysis for Pattern-Mixture Models
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    Chapter 21 How Ignorable Is Missing At Random?
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    Chapter 22 The Expectation-Maximization Algorithm
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    Chapter 23 Design Considerations
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    Chapter 24 Case Studies