Analysis of Incomplete Survey Data : Multiple Imputation via Bayesian Bootstrap Predictive Mean Matching
| Faculty/Professorship: | Fakultät Sozial- und Wirtschaftswissenschaften: Abschlussarbeiten |
| Author(s): | Meinfelder, Florian  |
| By: | Koller-Meinfelder, Florian |
| Alternative Title: | Analyse unvollständiger Befragungsdaten - Multiple Imputation mittels Bayesian Bootstrap Predictive Mean Matching |
| Publisher Information: | Bamberg : opus |
| Year of publication: | 2009 |
| Pages: | XVII, 145 |
| Supervisor(s): | Rässler, Susanne; Raghunathan, Trivellore E. |
| Language(s): | English |
| Remark: | Bamberg, Univ., Diss., 2009 |
| Licence: | German Act on Copyright |
| URN: | urn:nbn:de:bvb:473-opus-2251 |
| Abstract: | Multiple Imputation (MI) is a general purpose approach to impute partially incomplete data. The proposed method - Bayesian Bootstrap Predictive Mean Matching - is a variant that incorporates the robustifying properties of a nearest neighbour technique (Predictive Mean Matching) into MI. Multiple Imputation (MI) ist ein allgemeiner Ansatz zur Ergänzung fehlender Daten. Die vorgestellte Methode - Bayesian Bootstrap Predictive Mean Matching - ist eine MI-Variante, welche die robustifizierenden Eigenschaften eines Nearest-Neighbour-Verfahrens (Predictive Mean Matching) integriert. |
| GND Keywords: | Bayes-Entscheidungstheorie; Bootstrap-Statistik; Imputationstechnik |
| Keywords: | Datenergänzung , Multiple Imputation, missing data , multiple imputation , nearest neighbour matching, Datenergänzung, Multiple Imputation, missing data, multiple imputation, nearest neighbour matching |
| DDC Classification: | 510 Mathematics |
| RVK Classification: | QH 233 |
| Type: | Doctoralthesis |
| URI: | https://fis.uni-bamberg.de/handle/uniba/213 |
| Year of publication: | 25. January 2010 |
| Awards: | Promotionspreise der Hans-Löwel-Stiftung |
| File | Size | Format | |
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| Dokument_1.pdf | 5.95 MB | View/Open |
originated at the
University of Bamberg
University of Bamberg
