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Dedication
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Dedication
by Xaiobo Ding, Danping Lui, Chuan Zhou, Xiao-Hua Zhou
Applied Missing Data Analysis in the Health Sciences
Cover
Wiley Series in Statistics in Practice
Title Page
Copyright
Dedication
List of Figures
List of Tables
Preface
Chapter 1: Missing Data Concepts and Motivating Examples
1.1 Overview of the Missing Data Problem
1.2 Patterns and Mechanisms of Missing Data
1.3 Data Examples
Chapter 2: Overview of Methods for Dealing with Missing Data
2.1 Methods that Remove Observations
2.2 Methods that Utilize all Available Data
2.3 Methods that Impute Missing Values
2.4 Bayesian Methods
Chapter 3: Design Considerations in the Presence of Missing Data
3.1 Design Factors Related to Missing Data
3.2 Strategies for Limiting Missing Data in the Design of Clinical Trials
3.3 Strategies for Limiting Missing Data in the Conduct of Clinical Trials
3.4 Minimize the Impact of Missing Data
Chapter 4: Cross-sectional Data Methods
4.1 Overview of General Methods
4.2 Data Examples
4.3 Maximum Likelihood Approach
4.4 Bayesian Methods
4.5 Multiple Imputation
4.6 Imputing Estimating Equations
4.7 Inverse Probability Weighting
4.8 Doubly Robust Estimators
4.9 Code Used in This Chapter
Chapter 5: Longitudinal Data Methods
5.1 Overview
5.2 Examples
5.3 Longitudinal Regression Models for Complete Data
5.4 Missing Data Settings and Simple Methods
5.5 Likelihood Approach
5.6 Inverse Probability Weighted GEE with MAR Dropout
5.7 Extension to Nonmonotone Missingness
5.8 Multiple Imputation
5.9 Bayesian Inference
5.10 Other Approaches
Appendix 5.A: Technical Details of the Approximation Methods for GLMM and Computer Code for the Examples
Chapter 6: Survival Analysis under Ignorable Missingness
6.1 Overview
6.2 Introduction
6.3 Enhanced Complete-Case Analysis
6.4 Weighted Methods
6.5 Imputation Methods
6.6 Nonparametric Maximum Likelihood Estimation
6.7 Transformation Model
6.8 Data Example: Pathways Study
6.9 Concluding Remarks
Chapter 7: Nonignorable Missingness
7.1 Introduction
7.2 Cross-Sectional Data: Selection Model
7.3 Longitudinal Data with Dropout
7.4 Bayesian Analysis for Generalized Linear Models with Nonignorably Missing Covariates
7.5 Multiple Imputation
7.6 Inverse Probability Weighted Methods
Chapter 8: Analysis of Randomized Clinical Trials with Noncompliance
8.1 Overview
8.2 Examples
8.3 Some Common but Naive Methods
8.4 Notations, Assumptions, and Causal Definitions
8.5 Method of Instrumental Variables
8.6 Moment-based Method
8.7 Maximum Likelihood and Bayesian Methods
8.8 Noncompliance and Missing Outcome Data
8.9 Analysis of the Two Examples
8.10 Other Methods for Dealing with both Noncompliance and Missing Data
Appendix 8.A: Multivariate Delta Method
Bibliography
Index
End User License Agreement
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Copyright
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List of Figures
Dedication
To Yea-Jae, Yi,
Tingting, and Shuqin
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