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Applied Multiple Imputation: Advantages, Pitfalls, New Developments and Applications in R

Applied Multiple Imputation: Advantages, Pitfalls, New Developments and Applications in R

von Daniel Salfrán, Jost Reinecke, Kristian Kleinke, Martin Spiess
Hardcover - 9783030381639
85,59 €
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Beschreibung

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.

Details

Verlag Springer International Publishing
Ersterscheinung März 2020
Maße 241 mm x 160 mm x 22 mm
Gewicht 623 Gramm
Format Hardcover
ISBN-13 9783030381639
Auflage 1st ed. 2020
Seiten 304

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