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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
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Field name Details
Dewey Class 519.5
Title Applied Multiple Imputation ([EBook]) : Advantages, Pitfalls, New Developments and Applications in R / / by Kristian Kleinke, Jost Reinecke, Daniel Salfrán, Martin Spiess.
Author Kleinke, Kristian
Added Personal Name Reinecke, Jost
Salfrán, Daniel
Spiess, Martin
Other name(s) SpringerLink (Online service)
Edition statement 1st ed. 2020.
Publication Cham : : Springer International Publishing : : Imprint: Springer, , 2020.
Physical Details XI, 292 p. 23 illus., 3 illus. in color. : online resource.
Series Statistics for Social and Behavioral Sciences 2199-7357
ISBN 9783030381646
Summary Note 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. .:
Contents note 1 Introduction and Basic Concepts -- 2 Missing Data Mechanism and Ignorability -- 3 Missing Data Methods -- 4 Multiple Imputation: Theory -- 5 Multiple Imputation: Application -- 6 Multiple Imputation: New Developments -- A Appendices -- Index.
Mode of acces to digital resource Digital book. Cham Springer Nature 2020. - Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format
System details note - Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site https://doi.org/10.1007/978-3-030-38164-6
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