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Applied missing data analysis

Author: Craig K Enders
Publisher: New York : Guilford Press, ©2010.
Series: Methodology in the social sciences.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:
"Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and models for handling missing not at random (MNAR) data. Easy-to-follow  Read more...
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Craig K Enders
ISBN: 9781606236390 1606236393
OCLC Number: 456171131
Description: xv, 377 pages : illustrations ; 26 cm.
Contents: An introduction to missing data --
Traditional methods for dealing with missing data --
An introduction to maximum likelihood estimation --
Maximum likelihood missing data handling --
Improving the accuracy of maximum likelihood analyses --
An introduction to Bayesian estimation --
The imputation phase of multiple imputation --
The analysis and pooling phases of multiple Imputation --
Practical issues in multiple imputation --
Models for missing not at random data --
Wrapping things up : some final practical considerations.
Series Title: Methodology in the social sciences.
Responsibility: Craig K. Enders.
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Abstract:

Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their  Read more...

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"This is a well-written book that will be particularly useful for analysts who are not PhD statisticians. Enders provides a much-needed overview and explication of the current technical literature on Read more...

 
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