| Applied Multiple Imputation: Advantages, Pitfalls, New Developments and Applications in R 2020 Edition Contributor(s): Kleinke, Kristian (Author), Reinecke, Jost (Author), Salfrán, Daniel (Author) |
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ISBN: 3030381668 ISBN-13: 9783030381660 Publisher: Springer OUR PRICE: $66.49 Product Type: Paperback - Other Formats Published: March 2021 |
| Additional Information |
| BISAC Categories: - Social Science | Statistics - Psychology | Research & Methodology - Medical | Biostatistics |
| Physical Information: 0.64" H x 6.14" W x 9.21" (0.95 lbs) 292 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |