<電子ブック>
Missing Data : Analysis and Design / by John W. Graham
(Statistics for Social and Behavioral Sciences. ISSN:21997365)
版 | 1st ed. 2012. |
---|---|
出版者 | (New York, NY : Springer New York : Imprint: Springer) |
出版年 | 2012 |
本文言語 | 英語 |
大きさ | XXIV, 324 p : online resource |
著者標目 | *Graham, John W author SpringerLink (Online service) |
件 名 | LCSH:Social sciences -- Statistical methods
全ての件名で検索
LCSH:Statistics LCSH:Biometry FREE:Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy FREE:Statistics FREE:Biostatistics |
一般注記 | Missing Data Theory -- Multiple Imputation and Basic Analysis -- Practical Issues in Missing Data Analysis -- Planned Missing Data Design 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-effective planned missing data designs are provided. The author lays out missing data theory in a plain English style that is accessible and precise. Most analyses described in the book are conducted using the well-known statistical software packages SAS and SPSS, supplemented by Norm 2.03 and associated Java-based automation utilities. A related web site contains free downloads of the supplementary software, as well as sample empirical data sets and a variety of practical exercises described in the book to enhance and reinforce the reader’s learning experience. Missing Data: Analysis and Design and its web site work together to enable beginners to gain confidence in their ability to conduct missing data analysis, and more advanced readers to expandtheir skill set. JOHN W. GRAHAM, PhD, is Professor of Biobehavioral Health at The Pennsylvania State University. His research and publishing focus on the evaluation of health promotion and disease prevention interventions. He specializes in evaluation research methods, including missing data analysis and design, structural equation modeling, and measurement HTTP:URL=https://doi.org/10.1007/978-1-4614-4018-5 |
目次/あらすじ
所蔵情報を非表示
電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
電子ブック | オンライン | 電子ブック |
|
Springer eBooks | 9781461440185 |
|
電子リソース |
|
EB00236897 |
類似資料
この資料の利用統計
このページへのアクセス回数:3回
※2017年9月4日以降