Literaturnachweis - Detailanzeige
| Autor/in | Buuren, Stef van |
|---|---|
| Titel | Flexible imputation of missing data. |
| Quelle | Boca Raton, Fla. u.a.: CRC pr. (2012), XXV, 316 S. |
| Reihe | Chapman & Hall/CRC interdisciplinary statistics series |
| Beigaben | grafische Darstellungen; Literaturangaben S. 269-297 |
| Zusatzinformation | Inhaltsverzeichnis Inhaltsangabe |
| Sprache | englisch |
| Dokumenttyp | gedruckt; Monographie |
| ISBN | 1-4398-6824-7; 978-1-4398-6824-9 |
| Schlagwörter | Längsschnittuntersuchung; Methode; Multivariate Analyse; Algorithmus; Datenanalyse; Statistik; Anwendungsbeispiel; Daten; Fallbeispiel; Konzeption; Modell; Theorie |
| Abstract | Missing data form a problem in every scientific discipline, yet the techniques required to handle them are complicated and often lacking. One of the great ideas in statistical science-multiple imputation-fills gaps in the data with plausible values, the uncertainty of which is coded in the data itself. It also solves other problems, many of which are missing data problems in disguise. This book is supported by many examples using real data taken from the author's vast experience of collaborative research, and presents a practical guide for handling missing data under the framework of multiple imputation. Furthermore, detailed guidance of implementation in R using the author's package MICE is included throughout the book. Assuming familiarity with basic statistical concepts and multivariate methods, the book is intended for two audiences: 1. (Bio)statisticians, epidemiologists, and methodologists in the social and health sciences, 2. Substantive researchers who do not call themselves statisticians, but who possess the necessary skills to understand the principles and to follow the recipes. (DIPF/Orig.). |
| Erfasst von | DIPF | Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main |
| Update | 2013/1 |
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