| 书目名称 | Missing Data | | 副标题 | Analysis and Design | | 编辑 | John W. Graham | | 视频video | | | 概述 | Enables non-statisticians to implement modern missing data procedures properly in their research.Contains easy-to-read information for readers of all levels.Utilizes an accompanying website.Includes s | | 丛书名称 | Statistics for Social and Behavioral Sciences | | 图书封面 |  | | 描述 | .Missing data have long plagued those conducting applied research in the social, behavioral, and health sciences. Good missing data analysis solutions are available, but practical information about implementation of these solutions has been lacking. The objective of .Missing Data: Analysis and Design. is to enable investigators who are non-statisticians to implement modern missing data procedures properly in their research, and reap the benefits in terms of improved accuracy and statistical power.. .Missing Data: Analysis and Design. contains essential information for both beginners and advanced readers. For researchers with limited missing data analysis experience, this book offers an easy-to-read introduction to the theoretical underpinnings of analysis of missing data; provides clear, step-by-step instructions for performing state-of-the-art multiple imputation analyses; and offers practical advice, based on over 20 years‘ experience, for avoiding and troubleshooting problems. For more advanced readers, unique discussions of attrition, non-Monte-Carlo techniques for simulations involving missing data, evaluation of the benefits of auxiliary variables, and highly cost-effecti | | 出版日期 | Book 2012 | | 关键词 | Data analysis; Missing data; Monte Carlo; Multilevel data; Multiple imputation | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4614-4018-5 | | isbn_softcover | 978-1-4899-9573-5 | | isbn_ebook | 978-1-4614-4018-5Series ISSN 2199-7357 Series E-ISSN 2199-7365 | | issn_series | 2199-7357 | | copyright | Springer Science+Business Media New York 2012 |
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发表于 2025-3-21 17:39:12
