Multiple imputation and its application [electronic resource] James R. Carpenter and Michael G. Kenward.
Material type: TextSeries: Statistics in practicePublication details: Chichester, West Sussex, U.K. : Wiley, 2013.Edition: 1st edDescription: xviii, 345 p. : illSubject(s): Genre/Form: DDC classification:- 610.72/4 23
- QA276 .C37 2013
Item type | Current library | Call number | Status | Date due | Barcode | |
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Ebook | TUS: Midlands, Main Library Athlone Online | eBook (Browse shelf(Opens below)) | Available |
Includes bibliographical references and index.
Machine generated contents note: Reasons for missing data Summary -- The Multiple Imputation Procedure and Its Justification -- Multiple imputation of binary and ordinal data -- Imputation of unordered categorical data -- Non-linear relationships -- Interactions -- Survival data, skips and large datasets -- Multilevel multiple imputation -- Sensitivity analysis: MI unleashed -- Including survey weights -- Robust Multiple Imputation.
"This book is written with three main aims; to provide a thorough introduction to the general MI methods, to provide a detailed discussion of the practical use of the MI method and to present real-world examples drawn from the field of biostatistics"--Provided by publisher.
Electronic reproduction. Ann Arbor, MI : ProQuest, 2016. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.