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Missing Data

Overview of attention for book
Cover of 'Missing Data'

Table of Contents

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    Book Overview
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    Chapter 1 Missing Data Theory
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    Chapter 2 Analysis of Missing Data
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    Chapter 3 Multiple Imputation with Norm 2.03
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    Chapter 4 Analysis with SPSS (Versions Without MI Module) Following Multiple Imputation with Norm 2.03
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    Chapter 5 Multiple Imputation and Analysis with SPSS 17-20
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    Chapter 6 Multiple Imputation and Analysis with Multilevel (Cluster) Data
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    Chapter 7 Multiple Imputation and Analysis with SAS
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    Chapter 8 Practical Issues Relating to Analysis with Missing Data: Avoiding and Troubleshooting Problems
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    Chapter 9 Dealing with the Problem of Having Too Many Variables in the Imputation Model
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    Chapter 10 Simulations with Missing Data
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    Chapter 11 Using Modern Missing Data Methods with Auxiliary Variables to Mitigate the Effects of Attrition on Statistical Power
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    Chapter 12 Planned Missing Data Designs I: The 3-Form Design
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    Chapter 13 Planned Missing Data Design 2: Two-Method Measurement
Attention for Chapter 9: Dealing with the Problem of Having Too Many Variables in the Imputation Model
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