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Synopsis
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 examples and small simulated data sets illustrate the techniques and clarify the underlying principles. The companion website (www.appliedmissingdata.com) includes data files and syntax for the examples in the book as well as up-to-date information on software. The book is accessible to substantive researchers while providing a level of detail that will satisfy quantitative specialists.
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About the Author
Craig K. Enders is Associate Professor in the Quantitative Psychology concentration in the Department of Psychology at Arizona State University. The majority of his research focuses on analytic issues related to missing data analyses. He also does research in the area of structural equation modeling and multilevel modeling. Dr. Enders is a member of the American Psychological Association and is also active in the American Educational Research Association.
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Applied Missing Data Analysis (Methodology in the Social Sciences)
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The Guilford Press (edition First Edition), 2010
ISBN 10: 1606236393
ISBN 13: 9781606236390
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Applied Missing Data Analysis
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