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Missing Data

Overview of attention for book
Cover of 'Missing Data'

Table of Contents

  1. Altmetric Badge
    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 10: Simulations with Missing Data
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Citations

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Chapter title
Simulations with Missing Data
Chapter number 10
Book title
Missing Data
Published by
Springer, New York, NY, January 2012
DOI 10.1007/978-1-4614-4018-5_10
Book ISBNs
978-1-4614-4017-8, 978-1-4614-4018-5
Authors

John W. Graham, Graham, John W.

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 25%
Researcher 1 25%
Lecturer 1 25%
Student > Master 1 25%
Readers by discipline Count As %
Computer Science 1 25%
Psychology 1 25%
Economics, Econometrics and Finance 1 25%
Social Sciences 1 25%

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