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Flexible imputation of missing data /
~
Buuren, Stef van.
Flexible imputation of missing data /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Flexible imputation of missing data /Stef van Buuren.
作者:
Buuren, Stef van.
出版者:
Boca Raton, FL :CRC Press,c2012.
面頁冊數:
xxv, 316 p. :ill. (chiefly col.) ;25 cm.
標題:
Missing observations (Statistics)
ISBN:
9781439868249 (hardback) :
Flexible imputation of missing data /
Buuren, Stef van.
Flexible imputation of missing data /
Stef van Buuren. - Boca Raton, FL :CRC Press,c2012. - xxv, 316 p. :ill. (chiefly col.) ;25 cm. - Chapman & Hall/CRC interdisciplinary statistics series. - Interdisciplinary statistics..
Includes bibliographical references and indexes.
"Preface We are surrounded by missing data. Problems created by missing data in statistical analysis have long been swept under the carpet. These times are now slowly coming to an end. The array of techniques to deal with missing data has expanded considerably during the last decennia. This book is about one such method: multiple imputation. Multiple imputation is one of the great ideas in statistical science. The technique is simple, elegant and powerful. It is simple because it flls the holes in the data with plausible values. It is elegant because the uncertainty about the unknown data is coded in the data itself. And it is powerful because it can solve ’other’ problems that are actually missing data problems in disguise. Over the last 20 years, I have applied multiple imputation in a wide variety of projects. I believe the time is ripe for multiple imputation to enter mainstream statistics. Computers and software are now potent enough to do the required calculations with little e ort. What is still missing is a book that explains the basic ideas, and that shows how these ideas can be put to practice. My hope is that this book can ll this gap. The text assumes familiarity with basic statistical concepts and multivariate methods. The book is intended for two audiences: - (bio)statisticians, epidemiologists and methodologists in the social and health sciences; - substantive researchers who do not call themselves statisticians, but who possess the necessary skills to understand the principles and to follow the recipes. In writing this text, I have tried to avoid mathematical and technical details as far as possible. Formula’s are accompanied by a verbal statement that explains the formula in layman terms"--
ISBN: 9781439868249 (hardback) :NT$2676
LCCN: 2012000504
Nat. Bib. Agency Control No.: 015969781UkSubjects--Topical Terms:
182525
Missing observations (Statistics)
LC Class. No.: QA278 / .B88 2012
Dewey Class. No.: 519.5/35
Flexible imputation of missing data /
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"Preface We are surrounded by missing data. Problems created by missing data in statistical analysis have long been swept under the carpet. These times are now slowly coming to an end. The array of techniques to deal with missing data has expanded considerably during the last decennia. This book is about one such method: multiple imputation. Multiple imputation is one of the great ideas in statistical science. The technique is simple, elegant and powerful. It is simple because it flls the holes in the data with plausible values. It is elegant because the uncertainty about the unknown data is coded in the data itself. And it is powerful because it can solve ’other’ problems that are actually missing data problems in disguise. Over the last 20 years, I have applied multiple imputation in a wide variety of projects. I believe the time is ripe for multiple imputation to enter mainstream statistics. Computers and software are now potent enough to do the required calculations with little e ort. What is still missing is a book that explains the basic ideas, and that shows how these ideas can be put to practice. My hope is that this book can ll this gap. The text assumes familiarity with basic statistical concepts and multivariate methods. The book is intended for two audiences: - (bio)statisticians, epidemiologists and methodologists in the social and health sciences; - substantive researchers who do not call themselves statisticians, but who possess the necessary skills to understand the principles and to follow the recipes. In writing this text, I have tried to avoid mathematical and technical details as far as possible. Formula’s are accompanied by a verbal statement that explains the formula in layman terms"--
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