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Applied Multiple Imputation

Advantages, Pitfalls, New Developments and Applications in R

Jost Reinecke author Kristian Kleinke author Daniel Salfrán author Martin Spiess author

Format:Hardback

Publisher:Springer Nature Switzerland AG

Published:1st Mar '20

Currently unavailable, and unfortunately no date known when it will be back

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Applied Multiple Imputation cover

This book explores missing data techniques and provides a detailed and easy-to-read introduction to multiple imputation, covering the theoretical aspects of the topic and offering hands-on help with the implementation. It discusses the pros and cons of various techniques and concepts, including multiple imputation quality diagnostics, an important topic for practitioners. It also presents current research and new, practically relevant developments in the field, and demonstrates the use of recent multiple imputation techniques designed for situations where distributional assumptions of the classical multiple imputation solutions are violated. In addition, the book features numerous practical tutorials for widely used R software packages to generate multiple imputations (norm, pan and mice). The provided R code and data sets allow readers to reproduce all the examples and enhance their understanding of the procedures. This book is intended for social and health scientists and other quantitative researchers who analyze incompletely observed data sets, as well as master’s and PhD students with a sound basic knowledge of statistics. 

“This is an interesting book encouraging the application of the content presented.” (Maria de Ridder, ISCB News, iscb.info, Issue 70, December, 2020)

ISBN: 9783030381639

Dimensions: unknown

Weight: 623g

292 pages